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How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1: ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2: Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise more complex constructs.

Step 3: Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

Step 4: Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

Step 5: Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

Step 6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis. The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

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The Craft of Writing a Strong Hypothesis

Table of Contents

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good  alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

• Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
• Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher  the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

• A research hypothesis has to be simple yet clear to look justifiable enough.
• It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
• It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
• A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
• If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
• A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

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What is a Research Hypothesis: How to Write it, Types, and Examples

Any research begins with a research question and a research hypothesis . A research question alone may not suffice to design the experiment(s) needed to answer it. A hypothesis is central to the scientific method. But what is a hypothesis ? A hypothesis is a testable statement that proposes a possible explanation to a phenomenon, and it may include a prediction. Next, you may ask what is a research hypothesis ? Simply put, a research hypothesis is a prediction or educated guess about the relationship between the variables that you want to investigate.  

It is important to be thorough when developing your research hypothesis. Shortcomings in the framing of a hypothesis can affect the study design and the results. A better understanding of the research hypothesis definition and characteristics of a good hypothesis will make it easier for you to develop your own hypothesis for your research. Let’s dive in to know more about the types of research hypothesis , how to write a research hypothesis , and some research hypothesis examples .  

Table of Contents

What is a hypothesis ?  

A hypothesis is based on the existing body of knowledge in a study area. Framed before the data are collected, a hypothesis states the tentative relationship between independent and dependent variables, along with a prediction of the outcome.  

What is a research hypothesis ?  

Young researchers starting out their journey are usually brimming with questions like “ What is a hypothesis ?” “ What is a research hypothesis ?” “How can I write a good research hypothesis ?”   

A research hypothesis is a statement that proposes a possible explanation for an observable phenomenon or pattern. It guides the direction of a study and predicts the outcome of the investigation. A research hypothesis is testable, i.e., it can be supported or disproven through experimentation or observation.     

Characteristics of a good hypothesis  

Here are the characteristics of a good hypothesis :  

• Clearly formulated and free of language errors and ambiguity  
• Concise and not unnecessarily verbose  
• Has clearly defined variables  
• Testable and stated in a way that allows for it to be disproven  
• Can be tested using a research design that is feasible, ethical, and practical   
• Specific and relevant to the research problem  
• Rooted in a thorough literature search  
• Can generate new knowledge or understanding.  

How to create an effective research hypothesis  

A study begins with the formulation of a research question. A researcher then performs background research. This background information forms the basis for building a good research hypothesis . The researcher then performs experiments, collects, and analyzes the data, interprets the findings, and ultimately, determines if the findings support or negate the original hypothesis.  

Let’s look at each step for creating an effective, testable, and good research hypothesis :  

• Identify a research problem or question: Start by identifying a specific research problem.   
• Review the literature: Conduct an in-depth review of the existing literature related to the research problem to grasp the current knowledge and gaps in the field.   
• Formulate a clear and testable hypothesis : Based on the research question, use existing knowledge to form a clear and testable hypothesis . The hypothesis should state a predicted relationship between two or more variables that can be measured and manipulated. Improve the original draft till it is clear and meaningful.  
• State the null hypothesis: The null hypothesis is a statement that there is no relationship between the variables you are studying.   
• Define the population and sample: Clearly define the population you are studying and the sample you will be using for your research.  
• Select appropriate methods for testing the hypothesis: Select appropriate research methods, such as experiments, surveys, or observational studies, which will allow you to test your research hypothesis .  

Remember that creating a research hypothesis is an iterative process, i.e., you might have to revise it based on the data you collect. You may need to test and reject several hypotheses before answering the research problem.  

How to write a research hypothesis  

When you start writing a research hypothesis , you use an “if–then” statement format, which states the predicted relationship between two or more variables. Clearly identify the independent variables (the variables being changed) and the dependent variables (the variables being measured), as well as the population you are studying. Review and revise your hypothesis as needed.  

An example of a research hypothesis in this format is as follows:  

“ If [athletes] follow [cold water showers daily], then their [endurance] increases.”  

Population: athletes  

Independent variable: daily cold water showers  

Dependent variable: endurance  

You may have understood the characteristics of a good hypothesis . But note that a research hypothesis is not always confirmed; a researcher should be prepared to accept or reject the hypothesis based on the study findings.  

Research hypothesis checklist  

Following from above, here is a 10-point checklist for a good research hypothesis :  

• Testable: A research hypothesis should be able to be tested via experimentation or observation.  
• Specific: A research hypothesis should clearly state the relationship between the variables being studied.  
• Based on prior research: A research hypothesis should be based on existing knowledge and previous research in the field.  
• Falsifiable: A research hypothesis should be able to be disproven through testing.  
• Clear and concise: A research hypothesis should be stated in a clear and concise manner.  
• Logical: A research hypothesis should be logical and consistent with current understanding of the subject.  
• Relevant: A research hypothesis should be relevant to the research question and objectives.  
• Feasible: A research hypothesis should be feasible to test within the scope of the study.  
• Reflects the population: A research hypothesis should consider the population or sample being studied.  
• Uncomplicated: A good research hypothesis is written in a way that is easy for the target audience to understand.  

By following this research hypothesis checklist , you will be able to create a research hypothesis that is strong, well-constructed, and more likely to yield meaningful results.  

Types of research hypothesis  

Different types of research hypothesis are used in scientific research:  

1. Null hypothesis:

A null hypothesis states that there is no change in the dependent variable due to changes to the independent variable. This means that the results are due to chance and are not significant. A null hypothesis is denoted as H0 and is stated as the opposite of what the alternative hypothesis states.   

Example: “ The newly identified virus is not zoonotic .”  

2. Alternative hypothesis:

This states that there is a significant difference or relationship between the variables being studied. It is denoted as H1 or Ha and is usually accepted or rejected in favor of the null hypothesis.  

Example: “ The newly identified virus is zoonotic .”  

3. Directional hypothesis :

This specifies the direction of the relationship or difference between variables; therefore, it tends to use terms like increase, decrease, positive, negative, more, or less.   

Example: “ The inclusion of intervention X decreases infant mortality compared to the original treatment .”   

4. Non-directional hypothesis:

While it does not predict the exact direction or nature of the relationship between the two variables, a non-directional hypothesis states the existence of a relationship or difference between variables but not the direction, nature, or magnitude of the relationship. A non-directional hypothesis may be used when there is no underlying theory or when findings contradict previous research.  

Example, “ Cats and dogs differ in the amount of affection they express .”  

5. Simple hypothesis :

A simple hypothesis only predicts the relationship between one independent and another independent variable.  

Example: “ Applying sunscreen every day slows skin aging .”  

6 . Complex hypothesis :

A complex hypothesis states the relationship or difference between two or more independent and dependent variables.   

Example: “ Applying sunscreen every day slows skin aging, reduces sun burn, and reduces the chances of skin cancer .” (Here, the three dependent variables are slowing skin aging, reducing sun burn, and reducing the chances of skin cancer.)  

7. Associative hypothesis:  

An associative hypothesis states that a change in one variable results in the change of the other variable. The associative hypothesis defines interdependency between variables.  

Example: “ There is a positive association between physical activity levels and overall health .”  

8 . Causal hypothesis:

A causal hypothesis proposes a cause-and-effect interaction between variables.  

Example: “ Long-term alcohol use causes liver damage .”  

Note that some of the types of research hypothesis mentioned above might overlap. The types of hypothesis chosen will depend on the research question and the objective of the study.  

Research hypothesis examples  

Here are some good research hypothesis examples :  

“The use of a specific type of therapy will lead to a reduction in symptoms of depression in individuals with a history of major depressive disorder.”  

“Providing educational interventions on healthy eating habits will result in weight loss in overweight individuals.”  

“Plants that are exposed to certain types of music will grow taller than those that are not exposed to music.”  

“The use of the plant growth regulator X will lead to an increase in the number of flowers produced by plants.”  

Characteristics that make a research hypothesis weak are unclear variables, unoriginality, being too general or too vague, and being untestable. A weak hypothesis leads to weak research and improper methods.   

Some bad research hypothesis examples (and the reasons why they are “bad”) are as follows:  

“This study will show that treatment X is better than any other treatment . ” (This statement is not testable, too broad, and does not consider other treatments that may be effective.)  

“This study will prove that this type of therapy is effective for all mental disorders . ” (This statement is too broad and not testable as mental disorders are complex and different disorders may respond differently to different types of therapy.)  

“Plants can communicate with each other through telepathy . ” (This statement is not testable and lacks a scientific basis.)  

Importance of testable hypothesis  

If a research hypothesis is not testable, the results will not prove or disprove anything meaningful. The conclusions will be vague at best. A testable hypothesis helps a researcher focus on the study outcome and understand the implication of the question and the different variables involved. A testable hypothesis helps a researcher make precise predictions based on prior research.  

To be considered testable, there must be a way to prove that the hypothesis is true or false; further, the results of the hypothesis must be reproducible.  

Frequently Asked Questions (FAQs) on research hypothesis  

1. What is the difference between research question and research hypothesis ?  

A research question defines the problem and helps outline the study objective(s). It is an open-ended statement that is exploratory or probing in nature. Therefore, it does not make predictions or assumptions. It helps a researcher identify what information to collect. A research hypothesis , however, is a specific, testable prediction about the relationship between variables. Accordingly, it guides the study design and data analysis approach.

2. When to reject null hypothesis ?

A null hypothesis should be rejected when the evidence from a statistical test shows that it is unlikely to be true. This happens when the test statistic (e.g., p -value) is less than the defined significance level (e.g., 0.05). Rejecting the null hypothesis does not necessarily mean that the alternative hypothesis is true; it simply means that the evidence found is not compatible with the null hypothesis.  

3. How can I be sure my hypothesis is testable?  

A testable hypothesis should be specific and measurable, and it should state a clear relationship between variables that can be tested with data. To ensure that your hypothesis is testable, consider the following:  

• Clearly define the key variables in your hypothesis. You should be able to measure and manipulate these variables in a way that allows you to test the hypothesis.  
• The hypothesis should predict a specific outcome or relationship between variables that can be measured or quantified.   
• You should be able to collect the necessary data within the constraints of your study.  
• It should be possible for other researchers to replicate your study, using the same methods and variables.   
• Your hypothesis should be testable by using appropriate statistical analysis techniques, so you can draw conclusions, and make inferences about the population from the sample data.  
• The hypothesis should be able to be disproven or rejected through the collection of data.  

4. How do I revise my research hypothesis if my data does not support it?  

If your data does not support your research hypothesis , you will need to revise it or develop a new one. You should examine your data carefully and identify any patterns or anomalies, re-examine your research question, and/or revisit your theory to look for any alternative explanations for your results. Based on your review of the data, literature, and theories, modify your research hypothesis to better align it with the results you obtained. Use your revised hypothesis to guide your research design and data collection. It is important to remain objective throughout the process.  

5. I am performing exploratory research. Do I need to formulate a research hypothesis?  

As opposed to “confirmatory” research, where a researcher has some idea about the relationship between the variables under investigation, exploratory research (or hypothesis-generating research) looks into a completely new topic about which limited information is available. Therefore, the researcher will not have any prior hypotheses. In such cases, a researcher will need to develop a post-hoc hypothesis. A post-hoc research hypothesis is generated after these results are known.  

6. How is a research hypothesis different from a research question?

A research question is an inquiry about a specific topic or phenomenon, typically expressed as a question. It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis.

7. Can a research hypothesis change during the research process?

Yes, research hypotheses can change during the research process. As researchers collect and analyze data, new insights and information may emerge that require modification or refinement of the initial hypotheses. This can be due to unexpected findings, limitations in the original hypotheses, or the need to explore additional dimensions of the research topic. Flexibility is crucial in research, allowing for adaptation and adjustment of hypotheses to align with the evolving understanding of the subject matter.

8. How many hypotheses should be included in a research study?

The number of research hypotheses in a research study varies depending on the nature and scope of the research. It is not necessary to have multiple hypotheses in every study. Some studies may have only one primary hypothesis, while others may have several related hypotheses. The number of hypotheses should be determined based on the research objectives, research questions, and the complexity of the research topic. It is important to ensure that the hypotheses are focused, testable, and directly related to the research aims.

9. Can research hypotheses be used in qualitative research?

Yes, research hypotheses can be used in qualitative research, although they are more commonly associated with quantitative research. In qualitative research, hypotheses may be formulated as tentative or exploratory statements that guide the investigation. Instead of testing hypotheses through statistical analysis, qualitative researchers may use the hypotheses to guide data collection and analysis, seeking to uncover patterns, themes, or relationships within the qualitative data. The emphasis in qualitative research is often on generating insights and understanding rather than confirming or rejecting specific research hypotheses through statistical testing.

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How Do You Write an Hypothesis? Detailed Explanation and Examples

Writing a hypothesis is a fundamental step in the scientific research process. It serves as a tentative explanation or prediction that can be tested through experimentation and observation. A well-crafted hypothesis provides a clear direction for research and helps in drawing meaningful conclusions. This article will guide you through the process of writing a hypothesis, including understanding its concept, formulating it, and avoiding common pitfalls, with illustrative examples from various fields of study.

Key Takeaways

• A hypothesis is a testable and falsifiable statement that predicts an outcome based on certain conditions.
• There are different types of hypotheses, including null, alternative, and directional hypotheses, each serving a specific purpose in research.
• Formulating a hypothesis involves identifying research questions, conducting preliminary research, and crafting a clear and precise statement.
• A strong hypothesis is characterized by its testability, clarity, precision, and relevance to the research objectives.
• Common pitfalls in hypothesis writing include vague statements, overly complex hypotheses, and lack of testability.

Understanding the Concept of a Hypothesis

A hypothesis is a foundational element in scientific research, serving as a preliminary statement that proposes a potential relationship between variables. It is essential for guiding the direction of your study and providing a basis for data collection and analysis.

Steps to Formulate a Hypothesis

Identifying research questions.

The first step in formulating a hypothesis is to identify your research question . This involves observing the subject matter and recognizing patterns or relationships between variables. Crafting a clear, testable, and grounded hypothesis is essential for research success. By pinpointing the exact question you aim to answer, you lay the foundation for a focused and effective hypothesis.

Conducting Preliminary Research

Once you have your research question, the next step is to conduct preliminary research. This involves gathering as much information as possible about the topic. Evaluate these observations to identify potential causes and effects related to your research question. This stage helps you understand the existing knowledge and gaps, which is crucial for developing a well-informed hypothesis.

Formulating the Hypothesis Statement

After conducting preliminary research, you can begin formulating your hypothesis statement. This statement should clearly define the variables involved and the expected relationship between them. Ensure that your hypothesis is specific, testable, and falsifiable. A well-crafted hypothesis not only guides your research but also provides a clear direction for your experimental design and data collection methods.

Characteristics of a Strong Hypothesis

A strong hypothesis is essential for guiding your research and ensuring that your study is both meaningful and scientifically valid. Here are the key characteristics that define a robust hypothesis:

Testability and Falsifiability

A strong hypothesis must be testable, meaning you can design experiments to verify or refute it. Falsifiability is equally important; there should be a possibility to collect data that could disprove the hypothesis. This ensures that your hypothesis is grounded in empirical research rather than mere speculation.

Clarity and Precision

Your hypothesis should be clear and precise, leaving no room for ambiguity. This clarity helps in designing experiments and interpreting results. A well-defined hypothesis often begins with a specific research question and is articulated in simple, straightforward language.

Relevance to Research Objectives

A strong hypothesis is directly related to your research objectives. It should address the core question of your study and be aligned with the goals you aim to achieve. This relevance ensures that your hypothesis is not just an isolated statement but a crucial part of your overall research framework.

Common Pitfalls in Hypothesis Writing

When crafting a hypothesis, it's crucial to avoid common mistakes that can undermine your research. Vague statements are a frequent issue; they lack the specificity needed to be testable. For instance, saying "exercise improves health" is too broad. Instead, specify the type of exercise and the health outcome you are measuring.

Overly complex hypotheses can also be problematic. A hypothesis should be straightforward and focused. If it includes too many variables or conditions, it becomes difficult to test and analyze. Simplify your hypothesis to ensure clarity and feasibility.

Another major pitfall is the lack of testability. A hypothesis must be testable through empirical methods. If you cannot design an experiment or collect data to support or refute your hypothesis, it is not scientifically valid. Ensure your hypothesis can be tested with the resources and methods available to you.

Examples of Well-Written Hypotheses

In this section, you will explore various examples of well-crafted hypotheses across different fields of study. Understanding these examples will help you grasp the nuances of formulating a strong hypothesis.

Hypotheses in Natural Sciences

A well-written hypothesis in the natural sciences is both specific and testable. For instance, consider the hypothesis: "If plants are exposed to higher levels of sunlight, then their growth rate will increase." This statement clearly defines the variables and the expected relationship between them, making it a robust hypothesis for experimental testing.

Hypotheses in Social Sciences

In the social sciences, hypotheses often address complex human behaviors and societal trends. An example of a good hypothesis in this field is: "Individuals who participate in regular physical activity are more likely to report higher levels of mental well-being." This hypothesis is specific, testable, and relevant to the research objectives, providing a clear direction for the study.

Hypotheses in Applied Research

Applied research focuses on practical problem-solving. A strong hypothesis in this area might be: "Implementing a new software system will reduce the time required to complete administrative tasks by 20%." This hypothesis is not only testable but also directly applicable to real-world scenarios, making it highly valuable for applied research.

By examining these examples, you can better understand how to construct hypotheses that are clear, precise, and aligned with your research goals.

Testing and Refining Your Hypothesis

Designing experiments.

Before you dive into any experiment, you first formulate what you think will happen. This is where your hypothesis comes into play. A hypothesis in experimental design is essentially a testable prediction. Ensure that your hypothesis has clear and relevant variables, identifies the relationship between its variables, and is specific and testable. Designing a robust experiment involves controlling the independent variable and observing the dependent variable to validate or refute your hypothesis.

Data Collection Methods

Once your experiment is designed, the next step is to collect data. This involves choosing appropriate methods to gather data that will support or refute your hypothesis. Whether you use surveys, observations, or experiments, the key is to ensure that your data collection methods are reliable and valid. Remember, the priority of any scientific research is the conclusion, so collect data meticulously.

Analyzing Results and Making Adjustments

After data collection, the next step is to analyze the results. This involves statistical analysis to determine whether the data supports your hypothesis. If the data does not support your hypothesis, do not worry. This is a normal part of the scientific method. You may need to refine your hypothesis based on the findings. Use the results to identify weaknesses in your hypothesis and revise it if necessary. This iterative process helps in honing a more accurate and testable hypothesis.

The Importance of Hypotheses in Academic Writing

In academic writing, hypotheses serve as foundational elements that guide the direction and structure of your research. A well-formulated hypothesis not only provides a clear focus for your study but also helps in organizing your research methods and analysis. This is crucial for ensuring that your research remains coherent and targeted.

Guiding Research Direction

A hypothesis plays an important role in the scientific method by helping to create an appropriate experimental design. By establishing a specific, testable statement, you can streamline your research process and avoid unnecessary detours. This focused approach is essential for producing meaningful and reliable results.

Facilitating Critical Thinking

Formulating a hypothesis requires you to engage in critical thinking and problem-solving. This process helps you to clarify your research questions and objectives, making your study more robust and intellectually rigorous. It also encourages you to consider various outcomes and their implications, thereby enhancing the depth of your analysis.

Enhancing Academic Rigor

A well-constructed hypothesis adds a layer of academic rigor to your work. It demonstrates that you have a clear understanding of the theoretical framework and existing literature related to your topic. This not only strengthens your argument but also makes your research more credible and persuasive. In essence, a strong hypothesis is a testament to the quality and seriousness of your academic endeavor.

In academic writing, hypotheses play a crucial role in guiding research and providing a clear focus for your study. They help in formulating research questions and determining the direction of your investigation. If you're struggling with your thesis and need a structured approach, our Thesis Action Plan is here to help. Visit our website to claim your special offer now and overcome the challenges of thesis writing with ease.

In conclusion, writing a hypothesis is a fundamental step in the scientific research process that requires careful consideration and a structured approach. By observing the subject, identifying variables, and formulating a clear and testable statement, researchers can lay a solid foundation for their experiments. A well-crafted hypothesis not only guides the research but also provides a framework for analyzing results and drawing meaningful conclusions. As demonstrated in this article, understanding the components and steps involved in hypothesis writing is crucial for academic success and contributes significantly to the advancement of knowledge in various fields. By following the detailed explanations and examples provided, students and researchers can enhance their ability to construct effective hypotheses, thereby improving the quality and impact of their scientific inquiries.

Frequently Asked Questions

What is a hypothesis.

A hypothesis is a statement that predicts the outcome of a scientific study. It is an educated guess based on prior knowledge and observations.

Why is a hypothesis important in scientific research?

A hypothesis provides a focused direction for research. It helps researchers make predictions that can be tested through experiments and observations, thereby advancing scientific knowledge.

What are the types of hypotheses?

There are several types of hypotheses, including null hypotheses, alternative hypotheses, directional hypotheses, and non-directional hypotheses. Each serves a different purpose in research.

How do you formulate a hypothesis?

Formulating a hypothesis involves identifying a research question, conducting preliminary research, and then crafting a clear and testable statement that predicts an outcome.

What makes a hypothesis strong?

A strong hypothesis is testable, falsifiable, clear, precise, and relevant to the research objectives. It should be specific enough to be tested but broad enough to cover the scope of the research.

What are common pitfalls in writing a hypothesis?

Common pitfalls include making vague statements, creating overly complex hypotheses, and failing to ensure that the hypothesis is testable.

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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

• Operationalization

Hypothesis Types

Hypotheses examples.

• Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

• Forming a question
• Performing background research
• Creating a hypothesis
• Designing an experiment
• Collecting data
• Analyzing the results
• Drawing conclusions
• Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment  do not  support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the  journal articles you read . Many authors will suggest questions that still need to be explored.

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

• Collect as many observations about a topic or problem as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method ,  falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that  if  something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Importance of Operational Definitions

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

Hypothesis Checklist

• Does your hypothesis focus on something that you can actually test?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate the variables?
• Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

• Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
• Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
• Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
• Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
• Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the  dependent variable  if you change the  independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

• "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
• "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."​
• "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
• "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

Examples of a complex hypothesis include:

• "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
• "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

• "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
• "There is no difference in scores on a memory recall task between children and adults."
• "There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

• "People who take St. John's wort supplements will have less anxiety than those who do not."
• "Adults will perform better on a memory task than children."
• "Children who play first-person shooter games will show higher levels of aggression than children who do not." 

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as  case studies ,  naturalistic observations , and surveys are often used when  conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a  correlational study  can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods  are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually  cause  another to change.

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Thompson WH, Skau S. On the scope of scientific hypotheses .  R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:].  Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ?  PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies .  Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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How to Write a Research Hypothesis: Good & Bad Examples

What is a research hypothesis?

A research hypothesis is an attempt at explaining a phenomenon or the relationships between phenomena/variables in the real world. Hypotheses are sometimes called “educated guesses”, but they are in fact (or let’s say they should be) based on previous observations, existing theories, scientific evidence, and logic. A research hypothesis is also not a prediction—rather, predictions are ( should be) based on clearly formulated hypotheses. For example, “We tested the hypothesis that KLF2 knockout mice would show deficiencies in heart development” is an assumption or prediction, not a hypothesis. 

The research hypothesis at the basis of this prediction is “the product of the KLF2 gene is involved in the development of the cardiovascular system in mice”—and this hypothesis is probably (hopefully) based on a clear observation, such as that mice with low levels of Kruppel-like factor 2 (which KLF2 codes for) seem to have heart problems. From this hypothesis, you can derive the idea that a mouse in which this particular gene does not function cannot develop a normal cardiovascular system, and then make the prediction that we started with. 

What is the difference between a hypothesis and a prediction?

You might think that these are very subtle differences, and you will certainly come across many publications that do not contain an actual hypothesis or do not make these distinctions correctly. But considering that the formulation and testing of hypotheses is an integral part of the scientific method, it is good to be aware of the concepts underlying this approach. The two hallmarks of a scientific hypothesis are falsifiability (an evaluation standard that was introduced by the philosopher of science Karl Popper in 1934) and testability —if you cannot use experiments or data to decide whether an idea is true or false, then it is not a hypothesis (or at least a very bad one).

So, in a nutshell, you (1) look at existing evidence/theories, (2) come up with a hypothesis, (3) make a prediction that allows you to (4) design an experiment or data analysis to test it, and (5) come to a conclusion. Of course, not all studies have hypotheses (there is also exploratory or hypothesis-generating research), and you do not necessarily have to state your hypothesis as such in your paper. 

But for the sake of understanding the principles of the scientific method, let’s first take a closer look at the different types of hypotheses that research articles refer to and then give you a step-by-step guide for how to formulate a strong hypothesis for your own paper.

Types of Research Hypotheses

Hypotheses can be simple , which means they describe the relationship between one single independent variable (the one you observe variations in or plan to manipulate) and one single dependent variable (the one you expect to be affected by the variations/manipulation). If there are more variables on either side, you are dealing with a complex hypothesis. You can also distinguish hypotheses according to the kind of relationship between the variables you are interested in (e.g., causal or associative ). But apart from these variations, we are usually interested in what is called the “alternative hypothesis” and, in contrast to that, the “null hypothesis”. If you think these two should be listed the other way round, then you are right, logically speaking—the alternative should surely come second. However, since this is the hypothesis we (as researchers) are usually interested in, let’s start from there.

Alternative Hypothesis

If you predict a relationship between two variables in your study, then the research hypothesis that you formulate to describe that relationship is your alternative hypothesis (usually H1 in statistical terms). The goal of your hypothesis testing is thus to demonstrate that there is sufficient evidence that supports the alternative hypothesis, rather than evidence for the possibility that there is no such relationship. The alternative hypothesis is usually the research hypothesis of a study and is based on the literature, previous observations, and widely known theories. 

Null Hypothesis

The hypothesis that describes the other possible outcome, that is, that your variables are not related, is the null hypothesis ( H0 ). Based on your findings, you choose between the two hypotheses—usually that means that if your prediction was correct, you reject the null hypothesis and accept the alternative. Make sure, however, that you are not getting lost at this step of the thinking process: If your prediction is that there will be no difference or change, then you are trying to find support for the null hypothesis and reject H1. 

Directional Hypothesis

While the null hypothesis is obviously “static”, the alternative hypothesis can specify a direction for the observed relationship between variables—for example, that mice with higher expression levels of a certain protein are more active than those with lower levels. This is then called a one-tailed hypothesis. 

Another example for a directional one-tailed alternative hypothesis would be that 

H1: Attending private classes before important exams has a positive effect on performance. 

Your null hypothesis would then be that

H0: Attending private classes before important exams has no/a negative effect on performance.

Nondirectional Hypothesis

A nondirectional hypothesis does not specify the direction of the potentially observed effect, only that there is a relationship between the studied variables—this is called a two-tailed hypothesis. For instance, if you are studying a new drug that has shown some effects on pathways involved in a certain condition (e.g., anxiety) in vitro in the lab, but you can’t say for sure whether it will have the same effects in an animal model or maybe induce other/side effects that you can’t predict and potentially increase anxiety levels instead, you could state the two hypotheses like this:

H1: The only lab-tested drug (somehow) affects anxiety levels in an anxiety mouse model.

You then test this nondirectional alternative hypothesis against the null hypothesis:

H0: The only lab-tested drug has no effect on anxiety levels in an anxiety mouse model.

How to Write a Hypothesis for a Research Paper

Now that we understand the important distinctions between different kinds of research hypotheses, let’s look at a simple process of how to write a hypothesis.

Writing a Hypothesis Step:1

Ask a question, based on earlier research. Research always starts with a question, but one that takes into account what is already known about a topic or phenomenon. For example, if you are interested in whether people who have pets are happier than those who don’t, do a literature search and find out what has already been demonstrated. You will probably realize that yes, there is quite a bit of research that shows a relationship between happiness and owning a pet—and even studies that show that owning a dog is more beneficial than owning a cat ! Let’s say you are so intrigued by this finding that you wonder: 

What is it that makes dog owners even happier than cat owners? 

Let’s move on to Step 2 and find an answer to that question.

Writing a Hypothesis Step 2:

Formulate a strong hypothesis by answering your own question. Again, you don’t want to make things up, take unicorns into account, or repeat/ignore what has already been done. Looking at the dog-vs-cat papers your literature search returned, you see that most studies are based on self-report questionnaires on personality traits, mental health, and life satisfaction. What you don’t find is any data on actual (mental or physical) health measures, and no experiments. You therefore decide to make a bold claim come up with the carefully thought-through hypothesis that it’s maybe the lifestyle of the dog owners, which includes walking their dog several times per day, engaging in fun and healthy activities such as agility competitions, and taking them on trips, that gives them that extra boost in happiness. You could therefore answer your question in the following way:

Dog owners are happier than cat owners because of the dog-related activities they engage in.

Now you have to verify that your hypothesis fulfills the two requirements we introduced at the beginning of this resource article: falsifiability and testability . If it can’t be wrong and can’t be tested, it’s not a hypothesis. We are lucky, however, because yes, we can test whether owning a dog but not engaging in any of those activities leads to lower levels of happiness or well-being than owning a dog and playing and running around with them or taking them on trips.  

Writing a Hypothesis Step 3:

Make your predictions and define your variables. We have verified that we can test our hypothesis, but now we have to define all the relevant variables, design our experiment or data analysis, and make precise predictions. You could, for example, decide to study dog owners (not surprising at this point), let them fill in questionnaires about their lifestyle as well as their life satisfaction (as other studies did), and then compare two groups of active and inactive dog owners. Alternatively, if you want to go beyond the data that earlier studies produced and analyzed and directly manipulate the activity level of your dog owners to study the effect of that manipulation, you could invite them to your lab, select groups of participants with similar lifestyles, make them change their lifestyle (e.g., couch potato dog owners start agility classes, very active ones have to refrain from any fun activities for a certain period of time) and assess their happiness levels before and after the intervention. In both cases, your independent variable would be “ level of engagement in fun activities with dog” and your dependent variable would be happiness or well-being . 

Examples of a Good and Bad Hypothesis

Let’s look at a few examples of good and bad hypotheses to get you started.

Good Hypothesis Examples

Bad Hypothesis Examples

Tips for Writing a Research Hypothesis

If you understood the distinction between a hypothesis and a prediction we made at the beginning of this article, then you will have no problem formulating your hypotheses and predictions correctly. To refresh your memory: We have to (1) look at existing evidence, (2) come up with a hypothesis, (3) make a prediction, and (4) design an experiment. For example, you could summarize your dog/happiness study like this:

(1) While research suggests that dog owners are happier than cat owners, there are no reports on what factors drive this difference. (2) We hypothesized that it is the fun activities that many dog owners (but very few cat owners) engage in with their pets that increases their happiness levels. (3) We thus predicted that preventing very active dog owners from engaging in such activities for some time and making very inactive dog owners take up such activities would lead to an increase and decrease in their overall self-ratings of happiness, respectively. (4) To test this, we invited dog owners into our lab, assessed their mental and emotional well-being through questionnaires, and then assigned them to an “active” and an “inactive” group, depending on… 

Note that you use “we hypothesize” only for your hypothesis, not for your experimental prediction, and “would” or “if – then” only for your prediction, not your hypothesis. A hypothesis that states that something “would” affect something else sounds as if you don’t have enough confidence to make a clear statement—in which case you can’t expect your readers to believe in your research either. Write in the present tense, don’t use modal verbs that express varying degrees of certainty (such as may, might, or could ), and remember that you are not drawing a conclusion while trying not to exaggerate but making a clear statement that you then, in a way, try to disprove . And if that happens, that is not something to fear but an important part of the scientific process.

Similarly, don’t use “we hypothesize” when you explain the implications of your research or make predictions in the conclusion section of your manuscript, since these are clearly not hypotheses in the true sense of the word. As we said earlier, you will find that many authors of academic articles do not seem to care too much about these rather subtle distinctions, but thinking very clearly about your own research will not only help you write better but also ensure that even that infamous Reviewer 2 will find fewer reasons to nitpick about your manuscript. 

Perfect Your Manuscript With Professional Editing

Now that you know how to write a strong research hypothesis for your research paper, you might be interested in our free AI Proofreader , Wordvice AI, which finds and fixes errors in grammar, punctuation, and word choice in academic texts. Or if you are interested in human proofreading , check out our English editing services , including research paper editing and manuscript editing .

On the Wordvice academic resources website , you can also find many more articles and other resources that can help you with writing the other parts of your research paper , with making a research paper outline before you put everything together, or with writing an effective cover letter once you are ready to submit.

Research Hypothesis In Psychology: Types, & Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

A research hypothesis, in its plural form “hypotheses,” is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method .

Hypotheses connect theory to data and guide the research process towards expanding scientific understanding

Some key points about hypotheses:

• A hypothesis expresses an expected pattern or relationship. It connects the variables under investigation.
• It is stated in clear, precise terms before any data collection or analysis occurs. This makes the hypothesis testable.
• A hypothesis must be falsifiable. It should be possible, even if unlikely in practice, to collect data that disconfirms rather than supports the hypothesis.
• Hypotheses guide research. Scientists design studies to explicitly evaluate hypotheses about how nature works.
• For a hypothesis to be valid, it must be testable against empirical evidence. The evidence can then confirm or disprove the testable predictions.
• Hypotheses are informed by background knowledge and observation, but go beyond what is already known to propose an explanation of how or why something occurs.

Predictions typically arise from a thorough knowledge of the research literature, curiosity about real-world problems or implications, and integrating this to advance theory. They build on existing literature while providing new insight.

Types of Research Hypotheses

Alternative hypothesis.

The research hypothesis is often called the alternative or experimental hypothesis in experimental research.

It typically suggests a potential relationship between two key variables: the independent variable, which the researcher manipulates, and the dependent variable, which is measured based on those changes.

The alternative hypothesis states a relationship exists between the two variables being studied (one variable affects the other).

A hypothesis is a testable statement or prediction about the relationship between two or more variables. It is a key component of the scientific method. Some key points about hypotheses:

• Important hypotheses lead to predictions that can be tested empirically. The evidence can then confirm or disprove the testable predictions.

In summary, a hypothesis is a precise, testable statement of what researchers expect to happen in a study and why. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.

An experimental hypothesis predicts what change(s) will occur in the dependent variable when the independent variable is manipulated.

It states that the results are not due to chance and are significant in supporting the theory being investigated.

The alternative hypothesis can be directional, indicating a specific direction of the effect, or non-directional, suggesting a difference without specifying its nature. It’s what researchers aim to support or demonstrate through their study.

Null Hypothesis

The null hypothesis states no relationship exists between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to manipulating the independent variable.

It states results are due to chance and are not significant in supporting the idea being investigated.

The null hypothesis, positing no effect or relationship, is a foundational contrast to the research hypothesis in scientific inquiry. It establishes a baseline for statistical testing, promoting objectivity by initiating research from a neutral stance.

Many statistical methods are tailored to test the null hypothesis, determining the likelihood of observed results if no true effect exists.

This dual-hypothesis approach provides clarity, ensuring that research intentions are explicit, and fosters consistency across scientific studies, enhancing the standardization and interpretability of research outcomes.

Nondirectional Hypothesis

A non-directional hypothesis, also known as a two-tailed hypothesis, predicts that there is a difference or relationship between two variables but does not specify the direction of this relationship.

It merely indicates that a change or effect will occur without predicting which group will have higher or lower values.

For example, “There is a difference in performance between Group A and Group B” is a non-directional hypothesis.

Directional Hypothesis

A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e., greater, smaller, less, more)

It specifies whether one variable is greater, lesser, or different from another, rather than just indicating that there’s a difference without specifying its nature.

For example, “Exercise increases weight loss” is a directional hypothesis.

Falsifiability

The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory or hypothesis to be considered scientific, it must be testable and irrefutable.

Falsifiability emphasizes that scientific claims shouldn’t just be confirmable but should also have the potential to be proven wrong.

It means that there should exist some potential evidence or experiment that could prove the proposition false.

However many confirming instances exist for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.

For Popper, science should attempt to disprove a theory rather than attempt to continually provide evidence to support a research hypothesis.

Can a Hypothesis be Proven?

Hypotheses make probabilistic predictions. They state the expected outcome if a particular relationship exists. However, a study result supporting a hypothesis does not definitively prove it is true.

All studies have limitations. There may be unknown confounding factors or issues that limit the certainty of conclusions. Additional studies may yield different results.

In science, hypotheses can realistically only be supported with some degree of confidence, not proven. The process of science is to incrementally accumulate evidence for and against hypothesized relationships in an ongoing pursuit of better models and explanations that best fit the empirical data. But hypotheses remain open to revision and rejection if that is where the evidence leads.

• Disproving a hypothesis is definitive. Solid disconfirmatory evidence will falsify a hypothesis and require altering or discarding it based on the evidence.
• However, confirming evidence is always open to revision. Other explanations may account for the same results, and additional or contradictory evidence may emerge over time.

We can never 100% prove the alternative hypothesis. Instead, we see if we can disprove, or reject the null hypothesis.

If we reject the null hypothesis, this doesn’t mean that our alternative hypothesis is correct but does support the alternative/experimental hypothesis.

Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.

How to Write a Hypothesis

• Identify variables . The researcher manipulates the independent variable and the dependent variable is the measured outcome.
• Operationalized the variables being investigated . Operationalization of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression, you might count the number of punches given by participants.
• Decide on a direction for your prediction . If there is evidence in the literature to support a specific effect of the independent variable on the dependent variable, write a directional (one-tailed) hypothesis. If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
• Make it Testable : Ensure your hypothesis can be tested through experimentation or observation. It should be possible to prove it false (principle of falsifiability).
• Clear & concise language . A strong hypothesis is concise (typically one to two sentences long), and formulated using clear and straightforward language, ensuring it’s easily understood and testable.

Consider a hypothesis many teachers might subscribe to: students work better on Monday morning than on Friday afternoon (IV=Day, DV= Standard of work).

Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and a Friday afternoon and then measuring their immediate recall of the material covered in each session, we would end up with the following:

• The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
• The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.

More Examples

• Memory : Participants exposed to classical music during study sessions will recall more items from a list than those who studied in silence.
• Social Psychology : Individuals who frequently engage in social media use will report higher levels of perceived social isolation compared to those who use it infrequently.
• Developmental Psychology : Children who engage in regular imaginative play have better problem-solving skills than those who don’t.
• Clinical Psychology : Cognitive-behavioral therapy will be more effective in reducing symptoms of anxiety over a 6-month period compared to traditional talk therapy.
• Cognitive Psychology : Individuals who multitask between various electronic devices will have shorter attention spans on focused tasks than those who single-task.
• Health Psychology : Patients who practice mindfulness meditation will experience lower levels of chronic pain compared to those who don’t meditate.
• Organizational Psychology : Employees in open-plan offices will report higher levels of stress than those in private offices.
• Behavioral Psychology : Rats rewarded with food after pressing a lever will press it more frequently than rats who receive no reward.

How to Write a Hypothesis [31 Tips + Examples]

Writing hypotheses can seem tricky, but it’s essential for a solid scientific inquiry.

Here is a quick summary of how to write a hypothesis:

Write a hypothesis by clearly defining your research question, identifying independent and dependent variables, formulating a measurable prediction, and ensuring it can be tested through experimentation. Include an “if…then” statement for clarity.

I’ve crafted dozens in my research, from basic biology experiments to business marketing strategies.

Let me walk you through how to write a solid hypothesis, step by step.

Writing a Hypothesis: The Basics

Table of Contents

A hypothesis is a statement predicting the relationship between variables based on observations and existing knowledge. To craft a good hypothesis:

• Identify variables – Determine the independent and dependent variables involved.
• Predict relationships – Predict the interaction between these variables.
• Test the statement – Ensure the hypothesis is testable and falsifiable.

A solid hypothesis guides your research and sets the foundation for your experiment.

31 Tips for Writing a Hypothesis

There are at least 31 tips to write a good hypothesis.

Keep reading to learn every tip plus three examples to make sure that you can instantly apply it to your writing.

Tip 1: Start with a Clear Research Question

A clear research question ensures your hypothesis is targeted.

• Identify the broad topic you’re curious about, then refine it to a specific question.
• Use guiding questions like “What impact does variable X have on variable Y?”
• How does fertilizer affect plant growth?
• Does social media influence mental health in teens?
• Can personalized ads increase customer engagement?

Tip 2: Do Background Research

Research helps you understand current knowledge and any existing gaps.

• Review scholarly articles, reputable websites, and textbooks.
• Focus on understanding the relationships between variables in existing research.
• Academic journals like ScienceDirect or JSTOR.
• Google Scholar.
• Reputable news articles.

Tip 3: Identify Independent and Dependent Variables

The independent variable is what you change or control. The dependent variable is what you measure.

• Clearly define these variables to make your hypothesis precise.
• Think of different factors that could be influencing your dependent variable.
• Type of fertilizer (independent) and plant growth (dependent).
• Amount of screen time (independent) and anxiety levels (dependent).
• Marketing strategies (independent) and customer engagement (dependent).

Tip 4: Make Your Hypothesis Testable

A hypothesis must be measurable and falsifiable.

• Ensure your hypothesis can be supported or refuted through data collection.
• Include numerical variables or qualitative changes to ensure measurability.
• “Increasing screen time will increase anxiety levels in teenagers.”
• “Using fertilizer X will yield higher crop productivity.”
• “A/B testing marketing strategies will show higher engagement with personalized ads.”

Tip 5: Be Specific and Concise

Keep your hypothesis straightforward and to the point.

• Avoid vague terms that could mislead or cause confusion.
• Clearly outline what you’re measuring and how the variables interact.
• “Replacing chemical fertilizers with organic ones will result in slower plant growth.”
• “A social media break will decrease anxiety in high school students.”
• “Ads targeting user preferences will boost click-through rates by 10%.”

Tip 6: Choose Simple Language

Use simple, understandable language to ensure clarity.

• Avoid jargon and overly complex terms that could confuse readers.
• Make the hypothesis comprehensible to non-experts in the field.
• “Organic fertilizer will reduce plant growth.”
• “High schoolers will feel less anxious after a social media detox.”
• “Targeted ads will increase customer engagement.”

Tip 7: Formulate a Null Hypothesis

A null hypothesis assumes no relationship between variables.

• Create a counterpoint to your main hypothesis, asserting that there is no effect.
• This allows you to compare results directly and identify statistical significance.
• “Fertilizer type will not affect plant growth.”
• “Social media use will not influence anxiety.”
• “Targeted ads will not affect customer engagement.”

Tip 8: State Alternative Hypotheses

Provide alternative hypotheses to explore other plausible relationships.

• They offer a contingency plan if your primary hypothesis is not supported.
• These should still align with your research question and measurable variables.
• “Fertilizer X will only affect plant growth if used in specific soil types.”
• “Social media might impact anxiety only in certain age groups.”
• “Customer engagement might only improve with highly personalized ads.”

Tip 9: Use “If…Then” Statements

“If…then” statements simplify the cause-and-effect structure.

• The “if” clause identifies the independent variable, while “then” identifies the dependent.
• It makes your hypothesis easier to understand and directly testable.
• “If plants receive organic fertilizer, then their growth rate will slow.”
• “If teens stop using social media, then their anxiety will decrease.”
• “If ads are personalized, then click-through rates will increase.”

Tip 10: Avoid Assumptions

Don’t assume the audience understands your variables or relationships.

• Clearly define terms and relationships to avoid misinterpretation.
• Provide background context where necessary for clarity.
• Define “anxiety” as a feeling of worry or unease.
• Specify “plant growth” as the height and health of plants.
• Describe “personalized ads” as ads matching user preferences.

Tip 11: Review Existing Literature

Previous research offers insights into forming a hypothesis.

• Conduct a thorough literature review to identify trends and gaps.
• Use these studies to refine and build upon your hypothesis.
• Studies showing a link between screen time and anxiety.
• Research on organic versus chemical fertilizers.
• Customer behavior analysis in different marketing channels.

Tip 12: Consider Multiple Variables

Hypotheses with multiple variables can offer deeper insights.

• Explore combinations of independent and dependent variables to see their relationships.
• Plan experiments accordingly to distinguish separate effects.
• Studying fertilizer type and soil composition effects on plant growth.
• Testing social media use frequency and content type on anxiety.
• Analyzing marketing strategies combined with product preferences.

Tip 13: Review Ethical Considerations

Ethics are essential for trustworthy research.

• Avoid hypotheses that could cause harm to participants or the environment.
• Seek approval from relevant ethical boards or committees.
• Avoiding experiments causing undue stress to teenagers.
• Preventing chemical contamination when testing fertilizers.
• Respecting privacy with personalized ads.

Tip 14: Test with Pilot Studies

Small-scale pilot studies test feasibility and refine hypotheses.

• Use them to identify potential issues and adjust before full-scale research.
• Ensure pilot tests align with ethical standards.
• Testing different fertilizer types on small plant samples.
• Trying brief social media breaks with a small group of teens.
• Conducting A/B tests on ad personalization with a subset of customers.

Tip 15: Build Hypotheses on Existing Theories

Existing theories provide strong foundations.

• Use established frameworks to develop or refine your hypothesis.
• Testing theoretical predictions can yield meaningful data.
• Applying agricultural theories on soil and crop management.
• Using psychology theories on screen addiction and mental health.
• Referencing marketing theories like consumer behavior analysis.

Tip 16: Address Real-World Problems

Solve real-world problems through practical hypotheses.

• Make sure your research question has relevant, impactful applications.
• Focus on everyday challenges where actionable insights can help.
• Testing new eco-friendly farming methods.
• Reducing anxiety by improving digital wellbeing.
• Improving marketing ROI with personalized strategies.

Tip 17: Aim for Clear, Measurable Outcomes

The results should be easy to measure and interpret.

• Quantify your dependent variable or use defined qualitative measures.
• Avoid overly broad or ambiguous outcomes.
• Measuring plant growth as a percentage change in height.
• Quantifying anxiety levels through standard surveys.
• Tracking click-through rates as a percentage of total views.

Tip 18: Stay Open to Unexpected Results

Not all hypotheses yield expected results.

• Be open to learning new insights, even if they contradict your prediction.
• Unexpected findings often reveal unique, significant knowledge.
• Unexpected fertilizer types boosting growth differently than anticipated.
• Screen time affecting anxiety differently across various age groups.
• Targeted ads backfiring with specific customer segments.

Tip 19: Keep Hypotheses Relevant

Ensure your hypothesis aligns with the purpose of your research.

• Avoid straying from the original question or focusing on tangential issues.
• Stick to the research scope to ensure accurate and meaningful data.
• Focus on a specific type of fertilizer for plant growth.
• Restrict studies to relevant age groups for anxiety research.
• Keep marketing hypotheses within the same target customer segment.

Tip 20: Collaborate with Peers

Collaboration strengthens hypothesis development.

• Work with colleagues or mentors for valuable feedback.
• Peer review helps identify flaws or assumptions in your hypothesis.
• Reviewing hypothesis clarity with a lab partner.
• Sharing research plans with a mentor to refine focus.
• Engaging in academic peer-review groups.

Tip 21: Re-evaluate Hypotheses Periodically

Revising hypotheses ensures relevance.

• Update based on new literature, data, or technological advances.
• A dynamic approach keeps your research current.
• Refining fertilizer studies with recent organic farming research.
• Adjusting social media hypotheses for new platforms like TikTok.
• Modifying marketing hypotheses based on changing customer preferences.

Tip 22: Develop Compelling Visuals

Illustrating hypotheses can help communicate relationships effectively.

• Use diagrams or flowcharts to show how variables interact visually.
• Infographics make it easier for others to grasp your research concept.
• A flowchart showing fertilizer effects on different plant growth stages.
• Diagrams illustrating social media use and its psychological impact.
• Infographics depicting how various marketing strategies boost engagement.

Tip 23: Refine Your Data Collection Plan

A solid data collection plan is vital for a testable hypothesis.

• Determine the best ways to measure your dependent variable.
• Ensure your data collection tools are reliable and accurate.
• Using a ruler and image analysis software to measure plant height.
• Designing standardized surveys to assess anxiety levels consistently.
• Setting up click-through tracking with analytics software.

Tip 24: Focus on Logical Progression

Ensure your hypothesis logically follows your research question.

• The relationship between variables should naturally flow from your observations.
• Avoid logical leaps that might confuse your reasoning.
• Predicting plant growth after observing effects of different fertilizers.
• Linking anxiety to social media use based on screen time studies.
• Connecting ad personalization with customer behavior data.

Tip 25: Test Against Diverse Samples

Testing across diverse samples ensures broader applicability.

• Avoid drawing conclusions from overly narrow sample groups.
• Try to include different demographics or subgroups in your testing.
• Testing fertilizer effects on multiple plant species.
• Including different age groups in anxiety research.
• Experimenting with personalized ads across varied customer segments.

Tip 26: Use Control Groups

Control groups provide a baseline for comparison.

• Compare your test group with a control group under unchanged conditions.
• This allows you to isolate the effect of your independent variable.
• Comparing plant growth with organic versus no fertilizer.
• Testing anxiety levels with and without social media breaks.
• Comparing personalized ads with general marketing content.

Tip 27: Consider Practical Constraints

Work within realistic constraints for your resources and timeline.

• Assess the feasibility of testing your hypothesis.
• Modify the hypothesis if the required testing is unmanageable.
• Reducing fertilizer types to a manageable number for testing.
• Shortening social media detox periods to realistic durations.
• Targeting only specific marketing strategies to optimize testing.

Tip 28: Recognize Bias Risks

Biases can skew hypothesis formation.

• Acknowledge your assumptions and how they may affect your research.
• Minimize biases by clearly defining and measuring variables.
• Avoiding assumptions that organic fertilizer is inherently better.
• Ensuring survey questions don’t lead to specific anxiety outcomes.
• Testing marketing strategies objectively without favoring any method.

Tip 29: Prepare for Peer Review

Peer review ensures your hypothesis holds up to scrutiny.

• Provide a clear rationale for why your hypothesis is sound.
• Address potential criticisms to strengthen your research.
• Showing your plant growth study builds on existing fertilizer research.
• Demonstrating social media anxiety links through data and literature.
• Supporting your marketing hypotheses with solid behavioral data.

Tip 30: Create a Research Proposal

A proposal outlines your hypothesis, methodology, and significance.

• It ensures your hypothesis is clear and your methods are well-thought-out.
• Proposals also help secure funding or institutional approval.
• A proposal for fertilizer studies linking plant growth and soil health.
• Research plans connecting social media habits to anxiety measures.
• Marketing proposals tying customer behavior to personalized advertising.

Tip 31: Document Your Findings

Recording findings helps validate or challenge your hypothesis.

• Document the methodology, data, and conclusions clearly.
• This allows others to verify, replicate, or expand on your work.
• Recording fertilizer effects on plant height in different soil types.
• Survey results linking social media use with anxiety levels.
• Click-through data proving personalized ads’ impact on engagement.

Check out this really good video about how to write a hypothesis:

Hypothesis Examples for Different Situations

Let’s look at some examples of how to write a hypothesis in different circumstances.

• Marketing Analysis : “If personalized ads are shown to our target demographic, then click-through rates will increase by at least 10%.”
• Process Improvement : “If automated workflows replace manual data entry, then task completion times will decrease by 20%.”
• Product Development : “If adding a chatbot feature to our app increases customer support efficiency, then user satisfaction will improve by 15%.”
• Biology Experiment : “If students grow plants with different fertilizers, then the organic fertilizer will result in slower growth compared to the chemical fertilizer.”
• Psychology Research : “If high school students take a break from social media, then their levels of anxiety will decrease.”
• Environmental Study : “If a controlled forest area is exposed to a certain pollutant, then the local plant species will show signs of damage within two weeks.”

Professional Contacts

• Medical Research : “If a novel treatment method is applied to patients with chronic illness, then their recovery rate will increase significantly compared to standard treatment.”
• Technology Research : “If machine learning algorithms analyze big data sets, then the accuracy of predictive models will surpass traditional data analysis.”
• Engineering Project : “If new composite materials replace standard components in bridge construction, then the resulting structure will be more durable.”

Super Personal

• Gardening Experiment : “If different types of compost are used in home gardens, then plants receiving homemade compost will yield the most produce.”
• Fitness Routine : “If consistent strength training is combined with a high-protein diet, then muscle mass will increase more than with diet alone.”
• Cooking Techniques : “If searing is added before baking, then the resulting roast will retain more moisture.”

Final Thoughts: How to Write a Hypothesis

Crafting hypotheses is both a science and an art. It’s about channeling curiosity into testable questions that propel meaningful discovery.

Each well-thought-out hypothesis is a stepping stone that could lead to the breakthrough you’ve been seeking.

Stay curious and let your research journey unfold.

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Learn How To Write A Hypothesis For Your Next Research Project!

Undoubtedly, research plays a crucial role in substantiating or refuting our assumptions. These assumptions act as potential answers to our questions. Such assumptions, also known as hypotheses, are considered key aspects of research. In this blog, we delve into the significance of hypotheses. And provide insights on how to write them effectively. So, let’s dive in and explore the art of writing hypotheses together.

Table of Contents

What is a Hypothesis?

A hypothesis is a crucial starting point in scientific research. It is an educated guess about the relationship between two or more variables. In other words, a hypothesis acts as a foundation for a researcher to build their study.

Here are some examples of well-crafted hypotheses:

• Increased exposure to natural sunlight improves sleep quality in adults.

A positive relationship between natural sunlight exposure and sleep quality in adult individuals.

• Playing puzzle games on a regular basis enhances problem-solving abilities in children.

Engaging in frequent puzzle gameplay leads to improved problem-solving skills in children.

• Students and improved learning hecks.

S tudents using online  paper writing service  platforms (as a learning tool for receiving personalized feedback and guidance) will demonstrate improved writing skills. (compared to those who do not utilize such platforms).

• The use of APA format in research papers. 

Using the  APA format  helps students stay organized when writing research papers. Organized students can focus better on their topics and, as a result, produce better quality work.

The Building Blocks of a Hypothesis

To better understand the concept of a hypothesis, let’s break it down into its basic components:

• Variables . A hypothesis involves at least two variables. An independent variable and a dependent variable. The independent variable is the one being changed or manipulated, while the dependent variable is the one being measured or observed.
• Relationship : A hypothesis proposes a relationship or connection between the variables. This could be a cause-and-effect relationship or a correlation between them.
• Testability : A hypothesis should be testable and falsifiable, meaning it can be proven right or wrong through experimentation or observation.

Types of Hypotheses

When learning how to write a hypothesis, it’s essential to understand its main types. These include; alternative hypotheses and null hypotheses. In the following section, we explore both types of hypotheses with examples. 

Alternative Hypothesis (H1)

This kind of hypothesis suggests a relationship or effect between the variables. It is the main focus of the study. The researcher wants to either prove or disprove it. Many research divides this hypothesis into two subsections: 

• Directional 

This type of H1 predicts a specific outcome. Many researchers use this hypothesis to explore the relationship between variables rather than the groups. 

• Non-directional

You can take a guess from the name. This type of H1 does not provide a specific prediction for the research outcome. 

Here are some examples for your better understanding of how to write a hypothesis.

• Consuming caffeine improves cognitive performance.  (This hypothesis predicts that there is a positive relationship between caffeine consumption and cognitive performance.)
• Aerobic exercise leads to reduced blood pressure.  (This hypothesis suggests that engaging in aerobic exercise results in lower blood pressure readings.)
• Exposure to nature reduces stress levels among employees.  (Here, the hypothesis proposes that employees exposed to natural environments will experience decreased stress levels.)
• Listening to classical music while studying increases memory retention.  (This hypothesis speculates that studying with classical music playing in the background boosts students’ ability to retain information.)
• Early literacy intervention improves reading skills in children.  (This hypothesis claims that providing early literacy assistance to children results in enhanced reading abilities.)
• Time management in nursing students. ( Students who use a  nursing research paper writing service  have more time to focus on their studies and can achieve better grades in other subjects. )

Null Hypothesis (H0)

A null hypothesis assumes no relationship or effect between the variables. If the alternative hypothesis is proven to be false, the null hypothesis is considered to be true. Usually a null hypothesis shows no direct correlation between the defined variables. 

Here are some of the examples

• The consumption of herbal tea has no effect on sleep quality.  (This hypothesis assumes that herbal tea consumption does not impact the quality of sleep.)
• The number of hours spent playing video games is unrelated to academic performance.  (Here, the null hypothesis suggests that no relationship exists between video gameplay duration and academic achievement.)
• Implementing flexible work schedules has no influence on employee job satisfaction.  (This hypothesis contends that providing flexible schedules does not affect how satisfied employees are with their jobs.)
• Writing ability of a 7th grader is not affected by reading editorial example. ( There is no relationship between reading an  editorial example  and improving a 7th grader’s writing abilities.) 
• The type of lighting in a room does not affect people’s mood.  (In this null hypothesis, there is no connection between the kind of lighting in a room and the mood of those present.)
• The use of social media during break time does not impact productivity at work.  (This hypothesis proposes that social media usage during breaks has no effect on work productivity.)

As you learn how to write a hypothesis, remember that aiming for clarity, testability, and relevance to your research question is vital. By mastering this skill, you’re well on your way to conducting impactful scientific research. Good luck!

Importance of a Hypothesis in Research

A well-structured hypothesis is a vital part of any research project for several reasons:

• It provides clear direction for the study by setting its focus and purpose.
• It outlines expectations of the research, making it easier to measure results.
• It helps identify any potential limitations in the study, allowing researchers to refine their approach.

In conclusion, a hypothesis plays a fundamental role in the research process. By understanding its concept and constructing a well-thought-out hypothesis, researchers lay the groundwork for a successful, scientifically sound investigation.

How to Write a Hypothesis?

Here are five steps that you can follow to write an effective hypothesis. 

Step 1: Identify Your Research Question

The first step in learning how to compose a hypothesis is to clearly define your research question. This question is the central focus of your study and will help you determine the direction of your hypothesis.

Step 2: Determine the Variables

When exploring how to write a hypothesis, it’s crucial to identify the variables involved in your study. You’ll need at least two variables:

• Independent variable : The factor you manipulate or change in your experiment.
• Dependent variable : The outcome or result you observe or measure, which is influenced by the independent variable.

Step 3: Build the Hypothetical Relationship

In understanding how to compose a hypothesis, constructing the relationship between the variables is key. Based on your research question and variables, predict the expected outcome or connection. This prediction should be specific, testable, and, if possible, expressed in the “If…then” format.

Step 4: Write the Null Hypothesis

When mastering how to write a hypothesis, it’s important to create a null hypothesis as well. The null hypothesis assumes no relationship or effect between the variables, acting as a counterpoint to your primary hypothesis.

Step 5: Review Your Hypothesis

Finally, when learning how to compose a hypothesis, it’s essential to review your hypothesis for clarity, testability, and relevance to your research question. Make any necessary adjustments to ensure it provides a solid basis for your study.

In conclusion, understanding how to write a hypothesis is crucial for conducting successful scientific research. By focusing on your research question and carefully building relationships between variables, you will lay a strong foundation for advancing research and knowledge in your field.

Hypothesis vs. Prediction: What’s the Difference?

Understanding the differences between a hypothesis and a prediction is crucial in scientific research. Often, these terms are used interchangeably, but they have distinct meanings and functions. This segment aims to clarify these differences and explain how to compose a hypothesis correctly, helping you improve the quality of your research projects.

Hypothesis: The Foundation of Your Research

A hypothesis is an educated guess about the relationship between two or more variables. It provides the basis for your research question and is a starting point for an experiment or observational study.

The critical elements for a hypothesis include:

• Specificity: A clear and concise statement that describes the relationship between variables.
• Testability: The ability to test the hypothesis through experimentation or observation.

To learn how to write a hypothesis, it’s essential to identify your research question first and then predict the relationship between the variables.

Prediction: The Expected Outcome

A prediction is a statement about a specific outcome you expect to see in your experiment or observational study. It’s derived from the hypothesis and provides a measurable way to test the relationship between variables.

Here’s an example of how to write a hypothesis and a related prediction:

• Hypothesis: Consuming a high-sugar diet leads to weight gain.
• Prediction: People who consume a high-sugar diet for six weeks will gain more weight than those who maintain a low-sugar diet during the same period.

Key Differences Between a Hypothesis and a Prediction

While a hypothesis and prediction are both essential components of scientific research, there are some key differences to keep in mind:

• A hypothesis is an educated guess that suggests a relationship between variables, while a prediction is a specific and measurable outcome based on that hypothesis.
• A hypothesis can give rise to multiple experiment or observational study predictions.

To conclude, understanding the differences between a hypothesis and a prediction, and learning how to write a hypothesis, are essential steps to form a robust foundation for your research. By creating clear, testable hypotheses along with specific, measurable predictions, you lay the groundwork for scientifically sound investigations.

Here’s a wrap-up for this guide on how to write a hypothesis. We’re confident this article was helpful for many of you. We understand that many students struggle with writing their school research . However, we hope to continue assisting you through our blog tutorial on writing different aspects of academic assignments.

For further information, you can check out our reverent blog or contact our professionals to avail amazing writing services. Paper perk experts tailor assignments to reflect your unique voice and perspectives. Our professionals make sure to stick around till your satisfaction. So what are you waiting for? Pick your required service and order away!

How to write a good hypothesis?

How to write a hypothesis in science, how to write a research hypothesis, how to write a null hypothesis, what is the format for a scientific hypothesis, how do you structure a proper hypothesis, can you provide an example of a hypothesis, what is the ideal hypothesis structure.

The ideal hypothesis structure includes the following;

• A clear statement of the relationship between variables.
• testable prediction.
• falsifiability.

If your hypothesis has all of these, it is both scientifically sound and effective.

How to write a hypothesis for product management?

Writing a hypothesis for product management involves a simple process:

• First, identify the problem or question you want to address.
• State your assumption or belief about the solution to that problem. .
• Make a hypothesis by predicting a specific outcome based on your assumption.
• Make sure your hypothesis is specific, measurable, and testable.
• Use experiments, data analysis, or user feedback to validate your hypothesis.
• Make informed decisions for product improvement.

Following these steps will help you in effectively formulating hypotheses for product management.

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How to Write a Research Hypothesis

• Research Process
• Peer Review

Since grade school, we've all been familiar with hypotheses. The hypothesis is an essential step of the scientific method. But what makes an effective research hypothesis, how do you create one, and what types of hypotheses are there? We answer these questions and more.

Updated on April 27, 2022

What is a research hypothesis?

General hypothesis.

Since grade school, we've all been familiar with the term “hypothesis.” A hypothesis is a fact-based guess or prediction that has not been proven. It is an essential step of the scientific method. The hypothesis of a study is a drive for experimentation to either prove the hypothesis or dispute it.

Research Hypothesis

A research hypothesis is more specific than a general hypothesis. It is an educated, expected prediction of the outcome of a study that is testable.

What makes an effective research hypothesis?

A good research hypothesis is a clear statement of the relationship between a dependent variable(s) and independent variable(s) relevant to the study that can be disproven.

Research hypothesis checklist

Once you've written a possible hypothesis, make sure it checks the following boxes:

• It must be testable: You need a means to prove your hypothesis. If you can't test it, it's not a hypothesis.
• It must include a dependent and independent variable: At least one independent variable ( cause ) and one dependent variable ( effect ) must be included.
• The language must be easy to understand: Be as clear and concise as possible. Nothing should be left to interpretation.
• It must be relevant to your research topic: You probably shouldn't be talking about cats and dogs if your research topic is outer space. Stay relevant to your topic.

How to create an effective research hypothesis

Pose it as a question first.

Start your research hypothesis from a journalistic approach. Ask one of the five W's: Who, what, when, where, or why.

A possible initial question could be: Why is the sky blue?

Do the preliminary research

Once you have a question in mind, read research around your topic. Collect research from academic journals.

If you're looking for information about the sky and why it is blue, research information about the atmosphere, weather, space, the sun, etc.

Write a draft hypothesis

Once you're comfortable with your subject and have preliminary knowledge, create a working hypothesis. Don't stress much over this. Your first hypothesis is not permanent. Look at it as a draft.

Your first draft of a hypothesis could be: Certain molecules in the Earth's atmosphere are responsive to the sky being the color blue.

Make your working draft perfect

Take your working hypothesis and make it perfect. Narrow it down to include only the information listed in the “Research hypothesis checklist” above.

Now that you've written your working hypothesis, narrow it down. Your new hypothesis could be: Light from the sun hitting oxygen molecules in the sky makes the color of the sky appear blue.

Write a null hypothesis

Your null hypothesis should be the opposite of your research hypothesis. It should be able to be disproven by your research.

In this example, your null hypothesis would be: Light from the sun hitting oxygen molecules in the sky does not make the color of the sky appear blue.

Why is it important to have a clear, testable hypothesis?

One of the main reasons a manuscript can be rejected from a journal is because of a weak hypothesis. “Poor hypothesis, study design, methodology, and improper use of statistics are other reasons for rejection of a manuscript,” says Dr. Ish Kumar Dhammi and Dr. Rehan-Ul-Haq in Indian Journal of Orthopaedics.

According to Dr. James M. Provenzale in American Journal of Roentgenology , “The clear declaration of a research question (or hypothesis) in the Introduction is critical for reviewers to understand the intent of the research study. It is best to clearly state the study goal in plain language (for example, “We set out to determine whether condition x produces condition y.”) An insufficient problem statement is one of the more common reasons for manuscript rejection.”

Characteristics that make a hypothesis weak include:

• Unclear variables
• Unoriginality
• Too general
• Too specific

A weak hypothesis leads to weak research and methods . The goal of a paper is to prove or disprove a hypothesis - or to prove or disprove a null hypothesis. If the hypothesis is not a dependent variable of what is being studied, the paper's methods should come into question.

A strong hypothesis is essential to the scientific method. A hypothesis states an assumed relationship between at least two variables and the experiment then proves or disproves that relationship with statistical significance. Without a proven and reproducible relationship, the paper feeds into the reproducibility crisis. Learn more about writing for reproducibility .

In a study published in The Journal of Obstetrics and Gynecology of India by Dr. Suvarna Satish Khadilkar, she reviewed 400 rejected manuscripts to see why they were rejected. Her studies revealed that poor methodology was a top reason for the submission having a final disposition of rejection.

Aside from publication chances, Dr. Gareth Dyke believes a clear hypothesis helps efficiency.

“Developing a clear and testable hypothesis for your research project means that you will not waste time, energy, and money with your work,” said Dyke. “Refining a hypothesis that is both meaningful, interesting, attainable, and testable is the goal of all effective research.”

Types of research hypotheses

There can be overlap in these types of hypotheses.

Simple hypothesis

A simple hypothesis is a hypothesis at its most basic form. It shows the relationship of one independent and one independent variable.

Example: Drinking soda (independent variable) every day leads to obesity (dependent variable).

Complex hypothesis

A complex hypothesis shows the relationship of two or more independent and dependent variables.

Example: Drinking soda (independent variable) every day leads to obesity (dependent variable) and heart disease (dependent variable).

Directional hypothesis

A directional hypothesis guesses which way the results of an experiment will go. It uses words like increase, decrease, higher, lower, positive, negative, more, or less. It is also frequently used in statistics.

Example: Humans exposed to radiation have a higher risk of cancer than humans not exposed to radiation.

Non-directional hypothesis

A non-directional hypothesis says there will be an effect on the dependent variable, but it does not say which direction.

Associative hypothesis

An associative hypothesis says that when one variable changes, so does the other variable.

Alternative hypothesis

An alternative hypothesis states that the variables have a relationship.

• The opposite of a null hypothesis

Example: An apple a day keeps the doctor away.

Null hypothesis

A null hypothesis states that there is no relationship between the two variables. It is posed as the opposite of what the alternative hypothesis states.

Researchers use a null hypothesis to work to be able to reject it. A null hypothesis:

• Can never be proven
• Can only be rejected
• Is the opposite of an alternative hypothesis

Example: An apple a day does not keep the doctor away.

Logical hypothesis

A logical hypothesis is a suggested explanation while using limited evidence.

Example: Bats can navigate in the dark better than tigers.

In this hypothesis, the researcher knows that tigers cannot see in the dark, and bats mostly live in darkness.

Empirical hypothesis

An empirical hypothesis is also called a “working hypothesis.” It uses the trial and error method and changes around the independent variables.

• An apple a day keeps the doctor away.
• Two apples a day keep the doctor away.
• Three apples a day keep the doctor away.

In this case, the research changes the hypothesis as the researcher learns more about his/her research.

Statistical hypothesis

A statistical hypothesis is a look of a part of a population or statistical model. This type of hypothesis is especially useful if you are making a statement about a large population. Instead of having to test the entire population of Illinois, you could just use a smaller sample of people who live there.

Example: 70% of people who live in Illinois are iron deficient.

Causal hypothesis

A causal hypothesis states that the independent variable will have an effect on the dependent variable.

Example: Using tobacco products causes cancer.

Final thoughts

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How to Write a Hypothesis? Types and Examples 

All research studies involve the use of the scientific method, which is a mathematical and experimental technique used to conduct experiments by developing and testing a hypothesis or a prediction about an outcome. Simply put, a hypothesis is a suggested solution to a problem. It includes elements that are expressed in terms of relationships with each other to explain a condition or an assumption that hasn’t been verified using facts. 1 The typical steps in a scientific method include developing such a hypothesis, testing it through various methods, and then modifying it based on the outcomes of the experiments.  

A research hypothesis can be defined as a specific, testable prediction about the anticipated results of a study. 2 Hypotheses help guide the research process and supplement the aim of the study. After several rounds of testing, hypotheses can help develop scientific theories. 3 Hypotheses are often written as if-then statements. 

Here are two hypothesis examples: 

Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth. 4  

If a company offers flexible work hours, then their employees will be happier at work. 5  

Table of Contents

• What is a hypothesis? 
• Types of hypotheses 
• Characteristics of a hypothesis 
• Functions of a hypothesis 
• How to write a hypothesis 
• Hypothesis examples 
• Frequently asked questions 

What is a hypothesis?

A hypothesis expresses an expected relationship between variables in a study and is developed before conducting any research. Hypotheses are not opinions but rather are expected relationships based on facts and observations. They help support scientific research and expand existing knowledge. An incorrectly formulated hypothesis can affect the entire experiment leading to errors in the results so it’s important to know how to formulate a hypothesis and develop it carefully.

A few sources of a hypothesis include observations from prior studies, current research and experiences, competitors, scientific theories, and general conditions that can influence people. Figure 1 depicts the different steps in a research design and shows where exactly in the process a hypothesis is developed. 4  

There are seven different types of hypotheses—simple, complex, directional, nondirectional, associative and causal, null, and alternative. 

Types of hypotheses

The seven types of hypotheses are listed below: 5 , 6,7  

• Simple : Predicts the relationship between a single dependent variable and a single independent variable. 

Example: Exercising in the morning every day will increase your productivity.  

• Complex : Predicts the relationship between two or more variables. 

Example: Spending three hours or more on social media daily will negatively affect children’s mental health and productivity, more than that of adults.  

• Directional : Specifies the expected direction to be followed and uses terms like increase, decrease, positive, negative, more, or less. 

Example: The inclusion of intervention X decreases infant mortality compared to the original treatment.  

• Non-directional : Does not predict the exact direction, nature, or magnitude of the relationship between two variables but rather states the existence of a relationship. This hypothesis may be used when there is no underlying theory or if findings contradict prior research. 

Example: Cats and dogs differ in the amount of affection they express.  

• Associative and causal : An associative hypothesis suggests an interdependency between variables, that is, how a change in one variable changes the other.  

Example: There is a positive association between physical activity levels and overall health.  

A causal hypothesis, on the other hand, expresses a cause-and-effect association between variables. 

Example: Long-term alcohol use causes liver damage.  

• Null : Claims that the original hypothesis is false by showing that there is no relationship between the variables. 

Example: Sleep duration does not have any effect on productivity.  

• Alternative : States the opposite of the null hypothesis, that is, a relationship exists between two variables. 

Example: Sleep duration affects productivity.  

Characteristics of a hypothesis

So, what makes a good hypothesis? Here are some important characteristics of a hypothesis. 8,9  

• Testable : You must be able to test the hypothesis using scientific methods to either accept or reject the prediction. 
• Falsifiable : It should be possible to collect data that reject rather than support the hypothesis. 
• Logical : Hypotheses shouldn’t be a random guess but rather should be based on previous theories, observations, prior research, and logical reasoning. 
• Positive : The hypothesis statement about the existence of an association should be positive, that is, it should not suggest that an association does not exist. Therefore, the language used and knowing how to phrase a hypothesis is very important. 
• Clear and accurate : The language used should be easily comprehensible and use correct terminology. 
• Relevant : The hypothesis should be relevant and specific to the research question. 
• Structure : Should include all the elements that make a good hypothesis: variables, relationship, and outcome. 

Functions of a hypothesis

The following list mentions some important functions of a hypothesis: 1  

• Maintains the direction and progress of the research. 
• Expresses the important assumptions underlying the proposition in a single statement. 
• Establishes a suitable context for researchers to begin their investigation and for readers who are referring to the final report. 
• Provides an explanation for the occurrence of a specific phenomenon. 
• Ensures selection of appropriate and accurate facts necessary and relevant to the research subject. 

To summarize, a hypothesis provides the conceptual elements that complete the known data, conceptual relationships that systematize unordered elements, and conceptual meanings and interpretations that explain the unknown phenomena. 1  

How to write a hypothesis

Listed below are the main steps explaining how to write a hypothesis. 2,4,5  

• Make an observation and identify variables : Observe the subject in question and try to recognize a pattern or a relationship between the variables involved. This step provides essential background information to begin your research.  

For example, if you notice that an office’s vending machine frequently runs out of a specific snack, you may predict that more people in the office choose that snack over another. 

• Identify the main research question : After identifying a subject and recognizing a pattern, the next step is to ask a question that your hypothesis will answer.  

For example, after observing employees’ break times at work, you could ask “why do more employees take breaks in the morning rather than in the afternoon?” 

• Conduct some preliminary research to ensure originality and novelty : Your initial answer, which is your hypothesis, to the question is based on some pre-existing information about the subject. However, to ensure that your hypothesis has not been asked before or that it has been asked but rejected by other researchers you would need to gather additional information.  

For example, based on your observations you might state a hypothesis that employees work more efficiently when the air conditioning in the office is set at a lower temperature. However, during your preliminary research you find that this hypothesis was proven incorrect by a prior study. 

• Develop a general statement : After your preliminary research has confirmed the originality of your proposed answer, draft a general statement that includes all variables, subjects, and predicted outcome. The statement could be if/then or declarative.  
• Finalize the hypothesis statement : Use the PICOT model, which clarifies how to word a hypothesis effectively, when finalizing the statement. This model lists the important components required to write a hypothesis. 

P opulation: The specific group or individual who is the main subject of the research 

I nterest: The main concern of the study/research question 

C omparison: The main alternative group 

O utcome: The expected results  

T ime: Duration of the experiment 

Once you’ve finalized your hypothesis statement you would need to conduct experiments to test whether the hypothesis is true or false. 

Hypothesis examples

The following table provides examples of different types of hypotheses. 10 ,11  

Key takeaways  

Here’s a summary of all the key points discussed in this article about how to write a hypothesis. 

• A hypothesis is an assumption about an association between variables made based on limited evidence, which should be tested. 
• A hypothesis has four parts—the research question, independent variable, dependent variable, and the proposed relationship between the variables.   
• The statement should be clear, concise, testable, logical, and falsifiable. 
• There are seven types of hypotheses—simple, complex, directional, non-directional, associative and causal, null, and alternative. 
• A hypothesis provides a focus and direction for the research to progress. 
• A hypothesis plays an important role in the scientific method by helping to create an appropriate experimental design. 

Frequently asked questions

Hypotheses and research questions have different objectives and structure. The following table lists some major differences between the two. 9  

Here are a few examples to differentiate between a research question and hypothesis. 

Yes, here’s a simple checklist to help you gauge the effectiveness of your hypothesis. 9   1. When writing a hypothesis statement, check if it:  2. Predicts the relationship between the stated variables and the expected outcome.  3. Uses simple and concise language and is not wordy.  4. Does not assume readers’ knowledge about the subject.  5. Has observable, falsifiable, and testable results. 

As mentioned earlier in this article, a hypothesis is an assumption or prediction about an association between variables based on observations and simple evidence. These statements are usually generic. Research objectives, on the other hand, are more specific and dictated by hypotheses. The same hypothesis can be tested using different methods and the research objectives could be different in each case.     For example, Louis Pasteur observed that food lasts longer at higher altitudes, reasoned that it could be because the air at higher altitudes is cleaner (with fewer or no germs), and tested the hypothesis by exposing food to air cleaned in the laboratory. 12 Thus, a hypothesis is predictive—if the reasoning is correct, X will lead to Y—and research objectives are developed to test these predictions. 

Null hypothesis testing is a method to decide between two assumptions or predictions between variables (null and alternative hypotheses) in a statistical relationship in a sample. The null hypothesis, denoted as H 0 , claims that no relationship exists between variables in a population and any relationship in the sample reflects a sampling error or occurrence by chance. The alternative hypothesis, denoted as H 1 , claims that there is a relationship in the population. In every study, researchers need to decide whether the relationship in a sample occurred by chance or reflects a relationship in the population. This is done by hypothesis testing using the following steps: 13   1. Assume that the null hypothesis is true.  2. Determine how likely the sample relationship would be if the null hypothesis were true. This probability is called the p value.  3. If the sample relationship would be extremely unlikely, reject the null hypothesis and accept the alternative hypothesis. If the relationship would not be unlikely, accept the null hypothesis. 

To summarize, researchers should know how to write a good hypothesis to ensure that their research progresses in the required direction. A hypothesis is a testable prediction about any behavior or relationship between variables, usually based on facts and observation, and states an expected outcome.  

We hope this article has provided you with essential insight into the different types of hypotheses and their functions so that you can use them appropriately in your next research project. 

References  

• Dalen, DVV. The function of hypotheses in research. Proquest website. Accessed April 8, 2024. https://www.proquest.com/docview/1437933010?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals&imgSeq=1  
• McLeod S. Research hypothesis in psychology: Types & examples. SimplyPsychology website. Updated December 13, 2023. Accessed April 9, 2024. https://www.simplypsychology.org/what-is-a-hypotheses.html  
• Scientific method. Britannica website. Updated March 14, 2024. Accessed April 9, 2024. https://www.britannica.com/science/scientific-method  
• The hypothesis in science writing. Accessed April 10, 2024. https://berks.psu.edu/sites/berks/files/campus/HypothesisHandout_Final.pdf  
• How to develop a hypothesis (with elements, types, and examples). Indeed.com website. Updated February 3, 2023. Accessed April 10, 2024. https://www.indeed.com/career-advice/career-development/how-to-write-a-hypothesis  
• Types of research hypotheses. Excelsior online writing lab. Accessed April 11, 2024. https://owl.excelsior.edu/research/research-hypotheses/types-of-research-hypotheses/  
• What is a research hypothesis: how to write it, types, and examples. Researcher.life website. Published February 8, 2023. Accessed April 11, 2024. https://researcher.life/blog/article/how-to-write-a-research-hypothesis-definition-types-examples/  
• Developing a hypothesis. Pressbooks website. Accessed April 12, 2024. https://opentext.wsu.edu/carriecuttler/chapter/developing-a-hypothesis/  
• What is and how to write a good hypothesis in research. Elsevier author services website. Accessed April 12, 2024. https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/what-how-write-good-hypothesis-research/  
• How to write a great hypothesis. Verywellmind website. Updated March 12, 2023. Accessed April 13, 2024. https://www.verywellmind.com/what-is-a-hypothesis-2795239  
• 15 Hypothesis examples. Helpfulprofessor.com Published September 8, 2023. Accessed March 14, 2024. https://helpfulprofessor.com/hypothesis-examples/ 
• Editage insights. What is the interconnectivity between research objectives and hypothesis? Published February 24, 2021. Accessed April 13, 2024. https://www.editage.com/insights/what-is-the-interconnectivity-between-research-objectives-and-hypothesis  
• Understanding null hypothesis testing. BCCampus open publishing. Accessed April 16, 2024. https://opentextbc.ca/researchmethods/chapter/understanding-null-hypothesis-testing/#:~:text=In%20null%20hypothesis%20testing%2C%20this,said%20to%20be%20statistically%20significant  

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15 Hypothesis Examples

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Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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A hypothesis is defined as a testable prediction , and is used primarily in scientific experiments as a potential or predicted outcome that scientists attempt to prove or disprove (Atkinson et al., 2021; Tan, 2022).

In my types of hypothesis article, I outlined 13 different hypotheses, including the directional hypothesis (which makes a prediction about an effect of a treatment will be positive or negative) and the associative hypothesis (which makes a prediction about the association between two variables).

This article will dive into some interesting examples of hypotheses and examine potential ways you might test each one.

Hypothesis Examples

1. “inadequate sleep decreases memory retention”.

Field: Psychology

Type: Causal Hypothesis A causal hypothesis explores the effect of one variable on another. This example posits that a lack of adequate sleep causes decreased memory retention. In other words, if you are not getting enough sleep, your ability to remember and recall information may suffer.

How to Test:

To test this hypothesis, you might devise an experiment whereby your participants are divided into two groups: one receives an average of 8 hours of sleep per night for a week, while the other gets less than the recommended sleep amount.

During this time, all participants would daily study and recall new, specific information. You’d then measure memory retention of this information for both groups using standard memory tests and compare the results.

Should the group with less sleep have statistically significant poorer memory scores, the hypothesis would be supported.

Ensuring the integrity of the experiment requires taking into account factors such as individual health differences, stress levels, and daily nutrition.

Relevant Study: Sleep loss, learning capacity and academic performance (Curcio, Ferrara & De Gennaro, 2006)

2. “Increase in Temperature Leads to Increase in Kinetic Energy”

Field: Physics

Type: Deductive Hypothesis The deductive hypothesis applies the logic of deductive reasoning – it moves from a general premise to a more specific conclusion. This specific hypothesis assumes that as temperature increases, the kinetic energy of particles also increases – that is, when you heat something up, its particles move around more rapidly.

This hypothesis could be examined by heating a gas in a controlled environment and capturing the movement of its particles as a function of temperature.

You’d gradually increase the temperature and measure the kinetic energy of the gas particles with each increment. If the kinetic energy consistently rises with the temperature, your hypothesis gets supporting evidence.

Variables such as pressure and volume of the gas would need to be held constant to ensure validity of results.

3. “Children Raised in Bilingual Homes Develop Better Cognitive Skills”

Field: Psychology/Linguistics

Type: Comparative Hypothesis The comparative hypothesis posits a difference between two or more groups based on certain variables. In this context, you might propose that children raised in bilingual homes have superior cognitive skills compared to those raised in monolingual homes.

Testing this hypothesis could involve identifying two groups of children: those raised in bilingual homes, and those raised in monolingual homes.

Cognitive skills in both groups would be evaluated using a standard cognitive ability test at different stages of development. The examination would be repeated over a significant time period for consistency.

If the group raised in bilingual homes persistently scores higher than the other, the hypothesis would thereby be supported.

The challenge for the researcher would be controlling for other variables that could impact cognitive development, such as socio-economic status, education level of parents, and parenting styles.

Relevant Study: The cognitive benefits of being bilingual (Marian & Shook, 2012)

4. “High-Fiber Diet Leads to Lower Incidences of Cardiovascular Diseases”

Field: Medicine/Nutrition

Type: Alternative Hypothesis The alternative hypothesis suggests an alternative to a null hypothesis. In this context, the implied null hypothesis could be that diet has no effect on cardiovascular health, which the alternative hypothesis contradicts by suggesting that a high-fiber diet leads to fewer instances of cardiovascular diseases.

To test this hypothesis, a longitudinal study could be conducted on two groups of participants; one adheres to a high-fiber diet, while the other follows a diet low in fiber.

After a fixed period, the cardiovascular health of participants in both groups could be analyzed and compared. If the group following a high-fiber diet has a lower number of recorded cases of cardiovascular diseases, it would provide evidence supporting the hypothesis.

Control measures should be implemented to exclude the influence of other lifestyle and genetic factors that contribute to cardiovascular health.

Relevant Study: Dietary fiber, inflammation, and cardiovascular disease (King, 2005)

5. “Gravity Influences the Directional Growth of Plants”

Field: Agronomy / Botany

Type: Explanatory Hypothesis An explanatory hypothesis attempts to explain a phenomenon. In this case, the hypothesis proposes that gravity affects how plants direct their growth – both above-ground (toward sunlight) and below-ground (towards water and other resources).

The testing could be conducted by growing plants in a rotating cylinder to create artificial gravity.

Observations on the direction of growth, over a specified period, can provide insights into the influencing factors. If plants consistently direct their growth in a manner that indicates the influence of gravitational pull, the hypothesis is substantiated.

It is crucial to ensure that other growth-influencing factors, such as light and water, are uniformly distributed so that only gravity influences the directional growth.

6. “The Implementation of Gamified Learning Improves Students’ Motivation”

Field: Education

Type: Relational Hypothesis The relational hypothesis describes the relation between two variables. Here, the hypothesis is that the implementation of gamified learning has a positive effect on the motivation of students.

To validate this proposition, two sets of classes could be compared: one that implements a learning approach with game-based elements, and another that follows a traditional learning approach.

The students’ motivation levels could be gauged by monitoring their engagement, performance, and feedback over a considerable timeframe.

If the students engaged in the gamified learning context present higher levels of motivation and achievement, the hypothesis would be supported.

Control measures ought to be put into place to account for individual differences, including prior knowledge and attitudes towards learning.

Relevant Study: Does educational gamification improve students’ motivation? (Chapman & Rich, 2018)

7. “Mathematics Anxiety Negatively Affects Performance”

Field: Educational Psychology

Type: Research Hypothesis The research hypothesis involves making a prediction that will be tested. In this case, the hypothesis proposes that a student’s anxiety about math can negatively influence their performance in math-related tasks.

To assess this hypothesis, researchers must first measure the mathematics anxiety levels of a sample of students using a validated instrument, such as the Mathematics Anxiety Rating Scale.

Then, the students’ performance in mathematics would be evaluated through standard testing. If there’s a negative correlation between the levels of math anxiety and math performance (meaning as anxiety increases, performance decreases), the hypothesis would be supported.

It would be crucial to control for relevant factors such as overall academic performance and previous mathematical achievement.

8. “Disruption of Natural Sleep Cycle Impairs Worker Productivity”

Field: Organizational Psychology

Type: Operational Hypothesis The operational hypothesis involves defining the variables in measurable terms. In this example, the hypothesis posits that disrupting the natural sleep cycle, for instance through shift work or irregular working hours, can lessen productivity among workers.

To test this hypothesis, you could collect data from workers who maintain regular working hours and those with irregular schedules.

Measuring productivity could involve examining the worker’s ability to complete tasks, the quality of their work, and their efficiency.

If workers with interrupted sleep cycles demonstrate lower productivity compared to those with regular sleep patterns, it would lend support to the hypothesis.

Consideration should be given to potential confounding variables such as job type, worker age, and overall health.

9. “Regular Physical Activity Reduces the Risk of Depression”

Field: Health Psychology

Type: Predictive Hypothesis A predictive hypothesis involves making a prediction about the outcome of a study based on the observed relationship between variables. In this case, it is hypothesized that individuals who engage in regular physical activity are less likely to suffer from depression.

Longitudinal studies would suit to test this hypothesis, tracking participants’ levels of physical activity and their mental health status over time.

The level of physical activity could be self-reported or monitored, while mental health status could be assessed using standard diagnostic tools or surveys.

If data analysis shows that participants maintaining regular physical activity have a lower incidence of depression, this would endorse the hypothesis.

However, care should be taken to control other lifestyle and behavioral factors that could intervene with the results.

Relevant Study: Regular physical exercise and its association with depression (Kim, 2022)

10. “Regular Meditation Enhances Emotional Stability”

Type: Empirical Hypothesis In the empirical hypothesis, predictions are based on amassed empirical evidence . This particular hypothesis theorizes that frequent meditation leads to improved emotional stability, resonating with numerous studies linking meditation to a variety of psychological benefits.

Earlier studies reported some correlations, but to test this hypothesis directly, you’d organize an experiment where one group meditates regularly over a set period while a control group doesn’t.

Both groups’ emotional stability levels would be measured at the start and end of the experiment using a validated emotional stability assessment.

If regular meditators display noticeable improvements in emotional stability compared to the control group, the hypothesis gains credit.

You’d have to ensure a similar emotional baseline for all participants at the start to avoid skewed results.

11. “Children Exposed to Reading at an Early Age Show Superior Academic Progress”

Type: Directional Hypothesis The directional hypothesis predicts the direction of an expected relationship between variables. Here, the hypothesis anticipates that early exposure to reading positively affects a child’s academic advancement.

A longitudinal study tracking children’s reading habits from an early age and their consequent academic performance could validate this hypothesis.

Parents could report their children’s exposure to reading at home, while standardized school exam results would provide a measure of academic achievement.

If the children exposed to early reading consistently perform better acadically, it gives weight to the hypothesis.

However, it would be important to control for variables that might impact academic performance, such as socioeconomic background, parental education level, and school quality.

12. “Adopting Energy-efficient Technologies Reduces Carbon Footprint of Industries”

Field: Environmental Science

Type: Descriptive Hypothesis A descriptive hypothesis predicts the existence of an association or pattern related to variables. In this scenario, the hypothesis suggests that industries adopting energy-efficient technologies will resultantly show a reduced carbon footprint.

Global industries making use of energy-efficient technologies could track their carbon emissions over time. At the same time, others not implementing such technologies continue their regular tracking.

After a defined time, the carbon emission data of both groups could be compared. If industries that adopted energy-efficient technologies demonstrate a notable reduction in their carbon footprints, the hypothesis would hold strong.

In the experiment, you would exclude variations brought by factors such as industry type, size, and location.

13. “Reduced Screen Time Improves Sleep Quality”

Type: Simple Hypothesis The simple hypothesis is a prediction about the relationship between two variables, excluding any other variables from consideration. This example posits that by reducing time spent on devices like smartphones and computers, an individual should experience improved sleep quality.

A sample group would need to reduce their daily screen time for a pre-determined period. Sleep quality before and after the reduction could be measured using self-report sleep diaries and objective measures like actigraphy, monitoring movement and wakefulness during sleep.

If the data shows that sleep quality improved post the screen time reduction, the hypothesis would be validated.

Other aspects affecting sleep quality, like caffeine intake, should be controlled during the experiment.

Relevant Study: Screen time use impacts low‐income preschool children’s sleep quality, tiredness, and ability to fall asleep (Waller et al., 2021)

14. Engaging in Brain-Training Games Improves Cognitive Functioning in Elderly

Field: Gerontology

Type: Inductive Hypothesis Inductive hypotheses are based on observations leading to broader generalizations and theories. In this context, the hypothesis deduces from observed instances that engaging in brain-training games can help improve cognitive functioning in the elderly.

A longitudinal study could be conducted where an experimental group of elderly people partakes in regular brain-training games.

Their cognitive functioning could be assessed at the start of the study and at regular intervals using standard neuropsychological tests.

If the group engaging in brain-training games shows better cognitive functioning scores over time compared to a control group not playing these games, the hypothesis would be supported.

15. Farming Practices Influence Soil Erosion Rates

Type: Null Hypothesis A null hypothesis is a negative statement assuming no relationship or difference between variables. The hypothesis in this context asserts there’s no effect of different farming practices on the rates of soil erosion.

Comparing soil erosion rates in areas with different farming practices over a considerable timeframe could help test this hypothesis.

If, statistically, the farming practices do not lead to differences in soil erosion rates, the null hypothesis is accepted.

However, if marked variation appears, the null hypothesis is rejected, meaning farming practices do influence soil erosion rates. It would be crucial to control for external factors like weather, soil type, and natural vegetation.

The variety of hypotheses mentioned above underscores the diversity of research constructs inherent in different fields, each with its unique purpose and way of testing.

While researchers may develop hypotheses primarily as tools to define and narrow the focus of the study, these hypotheses also serve as valuable guiding forces for the data collection and analysis procedures, making the research process more efficient and direction-focused.

Hypotheses serve as a compass for any form of academic research. The diverse examples provided, from Psychology to Educational Studies, Environmental Science to Gerontology, clearly demonstrate how certain hypotheses suit specific fields more aptly than others.

It is important to underline that although these varied hypotheses differ in their structure and methods of testing, each endorses the fundamental value of empiricism in research. Evidence-based decision making remains at the heart of scholarly inquiry, regardless of the research field, thus aligning all hypotheses to the core purpose of scientific investigation.

Testing hypotheses is an essential part of the scientific method . By doing so, researchers can either confirm their predictions, giving further validity to an existing theory, or they might uncover new insights that could potentially shift the field’s understanding of a particular phenomenon. In either case, hypotheses serve as the stepping stones for scientific exploration and discovery.

Atkinson, P., Delamont, S., Cernat, A., Sakshaug, J. W., & Williams, R. A. (2021).  SAGE research methods foundations . SAGE Publications Ltd.

Curcio, G., Ferrara, M., & De Gennaro, L. (2006). Sleep loss, learning capacity and academic performance.  Sleep medicine reviews ,  10 (5), 323-337.

Kim, J. H. (2022). Regular physical exercise and its association with depression: A population-based study short title: Exercise and depression.  Psychiatry Research ,  309 , 114406.

King, D. E. (2005). Dietary fiber, inflammation, and cardiovascular disease.  Molecular nutrition & food research ,  49 (6), 594-600.

Marian, V., & Shook, A. (2012, September). The cognitive benefits of being bilingual. In Cerebrum: the Dana forum on brain science (Vol. 2012). Dana Foundation.

Tan, W. C. K. (2022). Research Methods: A Practical Guide For Students And Researchers (Second Edition) . World Scientific Publishing Company.

Waller, N. A., Zhang, N., Cocci, A. H., D’Agostino, C., Wesolek‐Greenson, S., Wheelock, K., … & Resnicow, K. (2021). Screen time use impacts low‐income preschool children’s sleep quality, tiredness, and ability to fall asleep. Child: care, health and development, 47 (5), 618-626.

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 25 Number Games for Kids (Free and Easy)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 25 Word Games for Kids (Free and Easy)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 25 Outdoor Games for Kids
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How to Write a Hypothesis

Last Updated: May 2, 2023 Fact Checked

This article was co-authored by Bess Ruff, MA . Bess Ruff is a Geography PhD student at Florida State University. She received her MA in Environmental Science and Management from the University of California, Santa Barbara in 2016. She has conducted survey work for marine spatial planning projects in the Caribbean and provided research support as a graduate fellow for the Sustainable Fisheries Group. There are 9 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 1,034,317 times.

A hypothesis is a description of a pattern in nature or an explanation about some real-world phenomenon that can be tested through observation and experimentation. The most common way a hypothesis is used in scientific research is as a tentative, testable, and falsifiable statement that explains some observed phenomenon in nature. [1] X Research source Many academic fields, from the physical sciences to the life sciences to the social sciences, use hypothesis testing as a means of testing ideas to learn about the world and advance scientific knowledge. Whether you are a beginning scholar or a beginning student taking a class in a science subject, understanding what hypotheses are and being able to generate hypotheses and predictions yourself is very important. These instructions will help get you started.

Preparing to Write a Hypothesis

• If you are writing a hypothesis for a school assignment, this step may be taken care of for you.

• Focus on academic and scholarly writing. You need to be certain that your information is unbiased, accurate, and comprehensive. Scholarly search databases such as Google Scholar and Web of Science can help you find relevant articles from reputable sources.
• You can find information in textbooks, at a library, and online. If you are in school, you can also ask for help from teachers, librarians, and your peers.

• For example, if you are interested in the effects of caffeine on the human body, but notice that nobody seems to have explored whether caffeine affects males differently than it does females, this could be something to formulate a hypothesis about. Or, if you are interested in organic farming, you might notice that no one has tested whether organic fertilizer results in different growth rates for plants than non-organic fertilizer.
• You can sometimes find holes in the existing literature by looking for statements like “it is unknown” in scientific papers or places where information is clearly missing. You might also find a claim in the literature that seems far-fetched, unlikely, or too good to be true, like that caffeine improves math skills. If the claim is testable, you could provide a great service to scientific knowledge by doing your own investigation. If you confirm the claim, the claim becomes even more credible. If you do not find support for the claim, you are helping with the necessary self-correcting aspect of science.
• Examining these types of questions provides an excellent way for you to set yourself apart by filling in important gaps in a field of study.

• Following the examples above, you might ask: "How does caffeine affect females as compared to males?" or "How does organic fertilizer affect plant growth compared to non-organic fertilizer?" The rest of your research will be aimed at answering these questions.

• Following the examples above, if you discover in the literature that there is a pattern that some other types of stimulants seem to affect females more than males, this could be a clue that the same pattern might be true for caffeine. Similarly, if you observe the pattern that organic fertilizer seems to be associated with smaller plants overall, you might explain this pattern with the hypothesis that plants exposed to organic fertilizer grow more slowly than plants exposed to non-organic fertilizer.

Formulating Your Hypothesis

• You can think of the independent variable as the one that is causing some kind of difference or effect to occur. In the examples, the independent variable would be biological sex, i.e. whether a person is male or female, and fertilizer type, i.e. whether the fertilizer is organic or non-organically-based.
• The dependent variable is what is affected by (i.e. "depends" on) the independent variable. In the examples above, the dependent variable would be the measured impact of caffeine or fertilizer.
• Your hypothesis should only suggest one relationship. Most importantly, it should only have one independent variable. If you have more than one, you won't be able to determine which one is actually the source of any effects you might observe.

• Don't worry too much at this point about being precise or detailed.
• In the examples above, one hypothesis would make a statement about whether a person's biological sex might impact the way the person is affected by caffeine; for example, at this point, your hypothesis might simply be: "a person's biological sex is related to how caffeine affects his or her heart rate." The other hypothesis would make a general statement about plant growth and fertilizer; for example your simple explanatory hypothesis might be "plants given different types of fertilizer are different sizes because they grow at different rates."

• Using our example, our non-directional hypotheses would be "there is a relationship between a person's biological sex and how much caffeine increases the person's heart rate," and "there is a relationship between fertilizer type and the speed at which plants grow."
• Directional predictions using the same example hypotheses above would be : "Females will experience a greater increase in heart rate after consuming caffeine than will males," and "plants fertilized with non-organic fertilizer will grow faster than those fertilized with organic fertilizer." Indeed, these predictions and the hypotheses that allow for them are very different kinds of statements. More on this distinction below.
• If the literature provides any basis for making a directional prediction, it is better to do so, because it provides more information. Especially in the physical sciences, non-directional predictions are often seen as inadequate.

• Where necessary, specify the population (i.e. the people or things) about which you hope to uncover new knowledge. For example, if you were only interested the effects of caffeine on elderly people, your prediction might read: "Females over the age of 65 will experience a greater increase in heart rate than will males of the same age." If you were interested only in how fertilizer affects tomato plants, your prediction might read: "Tomato plants treated with non-organic fertilizer will grow faster in the first three months than will tomato plants treated with organic fertilizer."

• For example, you would not want to make the hypothesis: "red is the prettiest color." This statement is an opinion and it cannot be tested with an experiment. However, proposing the generalizing hypothesis that red is the most popular color is testable with a simple random survey. If you do indeed confirm that red is the most popular color, your next step may be to ask: Why is red the most popular color? The answer you propose is your explanatory hypothesis .

• An easy way to get to the hypothesis for this method and prediction is to ask yourself why you think heart rates will increase if children are given caffeine. Your explanatory hypothesis in this case may be that caffeine is a stimulant. At this point, some scientists write a research hypothesis , a statement that includes the hypothesis, the experiment, and the prediction all in one statement.
• For example, If caffeine is a stimulant, and some children are given a drink with caffeine while others are given a drink without caffeine, then the heart rates of those children given a caffeinated drink will increase more than the heart rate of children given a non-caffeinated drink.

• Using the above example, if you were to test the effects of caffeine on the heart rates of children, evidence that your hypothesis is not true, sometimes called the null hypothesis , could occur if the heart rates of both the children given the caffeinated drink and the children given the non-caffeinated drink (called the placebo control) did not change, or lowered or raised with the same magnitude, if there was no difference between the two groups of children.
• It is important to note here that the null hypothesis actually becomes much more useful when researchers test the significance of their results with statistics. When statistics are used on the results of an experiment, a researcher is testing the idea of the null statistical hypothesis. For example, that there is no relationship between two variables or that there is no difference between two groups. [8] X Research source

Hypothesis Examples

Community Q&A

• Remember that science is not necessarily a linear process and can be approached in various ways. [10] X Research source Thanks Helpful 0 Not Helpful 0
• When examining the literature, look for research that is similar to what you want to do, and try to build on the findings of other researchers. But also look for claims that you think are suspicious, and test them yourself. Thanks Helpful 0 Not Helpful 0
• Be specific in your hypotheses, but not so specific that your hypothesis can't be applied to anything outside your specific experiment. You definitely want to be clear about the population about which you are interested in drawing conclusions, but nobody (except your roommates) will be interested in reading a paper with the prediction: "my three roommates will each be able to do a different amount of pushups." Thanks Helpful 0 Not Helpful 0

You Might Also Like

• ↑ https://undsci.berkeley.edu/for-educators/prepare-and-plan/correcting-misconceptions/#a4
• ↑ https://owl.purdue.edu/owl/general_writing/common_writing_assignments/research_papers/choosing_a_topic.html
• ↑ https://owl.purdue.edu/owl/subject_specific_writing/writing_in_the_social_sciences/writing_in_psychology_experimental_report_writing/experimental_reports_1.html
• ↑ https://www.grammarly.com/blog/how-to-write-a-hypothesis/
• ↑ https://grammar.yourdictionary.com/for-students-and-parents/how-create-hypothesis.html
• ↑ https://flexbooks.ck12.org/cbook/ck-12-middle-school-physical-science-flexbook-2.0/section/1.19/primary/lesson/hypothesis-ms-ps/
• ↑ https://iastate.pressbooks.pub/preparingtopublish/chapter/goal-1-contextualize-the-studys-methods/
• ↑ http://mathworld.wolfram.com/NullHypothesis.html
• ↑ http://undsci.berkeley.edu/article/scienceflowchart

About This Article

Before writing a hypothesis, think of what questions are still unanswered about a specific subject and make an educated guess about what the answer could be. Then, determine the variables in your question and write a simple statement about how they might be related. Try to focus on specific predictions and variables, such as age or segment of the population, to make your hypothesis easier to test. For tips on how to test your hypothesis, read on! Did this summary help you? Yes No

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What Is a Hypothesis and How Do I Write One?

General Education

Think about something strange and unexplainable in your life. Maybe you get a headache right before it rains, or maybe you think your favorite sports team wins when you wear a certain color. If you wanted to see whether these are just coincidences or scientific fact, you would form a hypothesis, then create an experiment to see whether that hypothesis is true or not.

But what is a hypothesis, anyway? If you’re not sure about what a hypothesis is--or how to test for one!--you’re in the right place. This article will teach you everything you need to know about hypotheses, including: 

• Defining the term “hypothesis” 
• Providing hypothesis examples 
• Giving you tips for how to write your own hypothesis

So let’s get started!

What Is a Hypothesis?

Merriam Webster defines a hypothesis as “an assumption or concession made for the sake of argument.” In other words, a hypothesis is an educated guess . Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it’s true or not. Keep in mind that in science, a hypothesis should be testable. You have to be able to design an experiment that tests your hypothesis in order for it to be valid. 

As you could assume from that statement, it’s easy to make a bad hypothesis. But when you’re holding an experiment, it’s even more important that your guesses be good...after all, you’re spending time (and maybe money!) to figure out more about your observation. That’s why we refer to a hypothesis as an educated guess--good hypotheses are based on existing data and research to make them as sound as possible.

Hypotheses are one part of what’s called the scientific method .  Every (good) experiment or study is based in the scientific method. The scientific method gives order and structure to experiments and ensures that interference from scientists or outside influences does not skew the results. It’s important that you understand the concepts of the scientific method before holding your own experiment. Though it may vary among scientists, the scientific method is generally made up of six steps (in order):

• Observation
• Asking questions
• Forming a hypothesis
• Analyze the data
• Communicate your results

You’ll notice that the hypothesis comes pretty early on when conducting an experiment. That’s because experiments work best when they’re trying to answer one specific question. And you can’t conduct an experiment until you know what you’re trying to prove!

Independent and Dependent Variables 

After doing your research, you’re ready for another important step in forming your hypothesis: identifying variables. Variables are basically any factor that could influence the outcome of your experiment . Variables have to be measurable and related to the topic being studied.

There are two types of variables:  independent variables and dependent variables. I ndependent variables remain constant . For example, age is an independent variable; it will stay the same, and researchers can look at different ages to see if it has an effect on the dependent variable. 

Speaking of dependent variables... dependent variables are subject to the influence of the independent variable , meaning that they are not constant. Let’s say you want to test whether a person’s age affects how much sleep they need. In that case, the independent variable is age (like we mentioned above), and the dependent variable is how much sleep a person gets. 

Variables will be crucial in writing your hypothesis. You need to be able to identify which variable is which, as both the independent and dependent variables will be written into your hypothesis. For instance, in a study about exercise, the independent variable might be the speed at which the respondents walk for thirty minutes, and the dependent variable would be their heart rate. In your study and in your hypothesis, you’re trying to understand the relationship between the two variables.

Elements of a Good Hypothesis

The best hypotheses start by asking the right questions . For instance, if you’ve observed that the grass is greener when it rains twice a week, you could ask what kind of grass it is, what elevation it’s at, and if the grass across the street responds to rain in the same way. Any of these questions could become the backbone of experiments to test why the grass gets greener when it rains fairly frequently.

As you’re asking more questions about your first observation, make sure you’re also making more observations . If it doesn’t rain for two weeks and the grass still looks green, that’s an important observation that could influence your hypothesis. You'll continue observing all throughout your experiment, but until the hypothesis is finalized, every observation should be noted.

Finally, you should consult secondary research before writing your hypothesis . Secondary research is comprised of results found and published by other people. You can usually find this information online or at your library. Additionally, m ake sure the research you find is credible and related to your topic. If you’re studying the correlation between rain and grass growth, it would help you to research rain patterns over the past twenty years for your county, published by a local agricultural association. You should also research the types of grass common in your area, the type of grass in your lawn, and whether anyone else has conducted experiments about your hypothesis. Also be sure you’re checking the quality of your research . Research done by a middle school student about what minerals can be found in rainwater would be less useful than an article published by a local university.

Writing Your Hypothesis

Once you’ve considered all of the factors above, you’re ready to start writing your hypothesis. Hypotheses usually take a certain form when they’re written out in a research report.

When you boil down your hypothesis statement, you are writing down your best guess and not the question at hand . This means that your statement should be written as if it is fact already, even though you are simply testing it.

The reason for this is that, after you have completed your study, you'll either accept or reject your if-then or your null hypothesis. All hypothesis testing examples should be measurable and able to be confirmed or denied. You cannot confirm a question, only a statement! 

In fact, you come up with hypothesis examples all the time! For instance, when you guess on the outcome of a basketball game, you don’t say, “Will the Miami Heat beat the Boston Celtics?” but instead, “I think the Miami Heat will beat the Boston Celtics.” You state it as if it is already true, even if it turns out you’re wrong. You do the same thing when writing your hypothesis.

Additionally, keep in mind that hypotheses can range from very specific to very broad.  These hypotheses can be specific, but if your hypothesis testing examples involve a broad range of causes and effects, your hypothesis can also be broad.  

The Two Types of Hypotheses

Now that you understand what goes into a hypothesis, it’s time to look more closely at the two most common types of hypothesis: the if-then hypothesis and the null hypothesis.

#1: If-Then Hypotheses

First of all, if-then hypotheses typically follow this formula:

If ____ happens, then ____ will happen.

The goal of this type of hypothesis is to test the causal relationship between the independent and dependent variable. It’s fairly simple, and each hypothesis can vary in how detailed it can be. We create if-then hypotheses all the time with our daily predictions. Here are some examples of hypotheses that use an if-then structure from daily life: 

• If I get enough sleep, I’ll be able to get more work done tomorrow.
• If the bus is on time, I can make it to my friend’s birthday party. 
• If I study every night this week, I’ll get a better grade on my exam. 

In each of these situations, you’re making a guess on how an independent variable (sleep, time, or studying) will affect a dependent variable (the amount of work you can do, making it to a party on time, or getting better grades). 

You may still be asking, “What is an example of a hypothesis used in scientific research?” Take one of the hypothesis examples from a real-world study on whether using technology before bed affects children’s sleep patterns. The hypothesis read s:

“We hypothesized that increased hours of tablet- and phone-based screen time at bedtime would be inversely correlated with sleep quality and child attention.”

It might not look like it, but this is an if-then statement. The researchers basically said, “If children have more screen usage at bedtime, then their quality of sleep and attention will be worse.” The sleep quality and attention are the dependent variables and the screen usage is the independent variable. (Usually, the independent variable comes after the “if” and the dependent variable comes after the “then,” as it is the independent variable that affects the dependent variable.) This is an excellent example of how flexible hypothesis statements can be, as long as the general idea of “if-then” and the independent and dependent variables are present.

#2: Null Hypotheses

Your if-then hypothesis is not the only one needed to complete a successful experiment, however. You also need a null hypothesis to test it against. In its most basic form, the null hypothesis is the opposite of your if-then hypothesis . When you write your null hypothesis, you are writing a hypothesis that suggests that your guess is not true, and that the independent and dependent variables have no relationship .

One null hypothesis for the cell phone and sleep study from the last section might say: 

“If children have more screen usage at bedtime, their quality of sleep and attention will not be worse.” 

In this case, this is a null hypothesis because it’s asking the opposite of the original thesis! 

Conversely, if your if-then hypothesis suggests that your two variables have no relationship, then your null hypothesis would suggest that there is one. So, pretend that there is a study that is asking the question, “Does the amount of followers on Instagram influence how long people spend on the app?” The independent variable is the amount of followers, and the dependent variable is the time spent. But if you, as the researcher, don’t think there is a relationship between the number of followers and time spent, you might write an if-then hypothesis that reads:

“If people have many followers on Instagram, they will not spend more time on the app than people who have less.”

In this case, the if-then suggests there isn’t a relationship between the variables. In that case, one of the null hypothesis examples might say:

“If people have many followers on Instagram, they will spend more time on the app than people who have less.”

You then test both the if-then and the null hypothesis to gauge if there is a relationship between the variables, and if so, how much of a relationship. 

4 Tips to Write the Best Hypothesis

If you’re going to take the time to hold an experiment, whether in school or by yourself, you’re also going to want to take the time to make sure your hypothesis is a good one. The best hypotheses have four major elements in common: plausibility, defined concepts, observability, and general explanation.

#1: Plausibility

At first glance, this quality of a hypothesis might seem obvious. When your hypothesis is plausible, that means it’s possible given what we know about science and general common sense. However, improbable hypotheses are more common than you might think. 

Imagine you’re studying weight gain and television watching habits. If you hypothesize that people who watch more than  twenty hours of television a week will gain two hundred pounds or more over the course of a year, this might be improbable (though it’s potentially possible). Consequently, c ommon sense can tell us the results of the study before the study even begins.

Improbable hypotheses generally go against  science, as well. Take this hypothesis example: 

“If a person smokes one cigarette a day, then they will have lungs just as healthy as the average person’s.” 

This hypothesis is obviously untrue, as studies have shown again and again that cigarettes negatively affect lung health. You must be careful that your hypotheses do not reflect your own personal opinion more than they do scientifically-supported findings. This plausibility points to the necessity of research before the hypothesis is written to make sure that your hypothesis has not already been disproven.

#2: Defined Concepts

The more advanced you are in your studies, the more likely that the terms you’re using in your hypothesis are specific to a limited set of knowledge. One of the hypothesis testing examples might include the readability of printed text in newspapers, where you might use words like “kerning” and “x-height.” Unless your readers have a background in graphic design, it’s likely that they won’t know what you mean by these terms. Thus, it’s important to either write what they mean in the hypothesis itself or in the report before the hypothesis.

Here’s what we mean. Which of the following sentences makes more sense to the common person?

If the kerning is greater than average, more words will be read per minute.

If the space between letters is greater than average, more words will be read per minute.

For people reading your report that are not experts in typography, simply adding a few more words will be helpful in clarifying exactly what the experiment is all about. It’s always a good idea to make your research and findings as accessible as possible. 

Good hypotheses ensure that you can observe the results. 

#3: Observability

In order to measure the truth or falsity of your hypothesis, you must be able to see your variables and the way they interact. For instance, if your hypothesis is that the flight patterns of satellites affect the strength of certain television signals, yet you don’t have a telescope to view the satellites or a television to monitor the signal strength, you cannot properly observe your hypothesis and thus cannot continue your study.

Some variables may seem easy to observe, but if you do not have a system of measurement in place, you cannot observe your hypothesis properly. Here’s an example: if you’re experimenting on the effect of healthy food on overall happiness, but you don’t have a way to monitor and measure what “overall happiness” means, your results will not reflect the truth. Monitoring how often someone smiles for a whole day is not reasonably observable, but having the participants state how happy they feel on a scale of one to ten is more observable. 

In writing your hypothesis, always keep in mind how you'll execute the experiment.

#4: Generalizability 

Perhaps you’d like to study what color your best friend wears the most often by observing and documenting the colors she wears each day of the week. This might be fun information for her and you to know, but beyond you two, there aren’t many people who could benefit from this experiment. When you start an experiment, you should note how generalizable your findings may be if they are confirmed. Generalizability is basically how common a particular phenomenon is to other people’s everyday life.

Let’s say you’re asking a question about the health benefits of eating an apple for one day only, you need to realize that the experiment may be too specific to be helpful. It does not help to explain a phenomenon that many people experience. If you find yourself with too specific of a hypothesis, go back to asking the big question: what is it that you want to know, and what do you think will happen between your two variables?

Hypothesis Testing Examples

We know it can be hard to write a good hypothesis unless you’ve seen some good hypothesis examples. We’ve included four hypothesis examples based on some made-up experiments. Use these as templates or launch pads for coming up with your own hypotheses.

Experiment #1: Students Studying Outside (Writing a Hypothesis)

You are a student at PrepScholar University. When you walk around campus, you notice that, when the temperature is above 60 degrees, more students study in the quad. You want to know when your fellow students are more likely to study outside. With this information, how do you make the best hypothesis possible?

You must remember to make additional observations and do secondary research before writing your hypothesis. In doing so, you notice that no one studies outside when it’s 75 degrees and raining, so this should be included in your experiment. Also, studies done on the topic beforehand suggested that students are more likely to study in temperatures less than 85 degrees. With this in mind, you feel confident that you can identify your variables and write your hypotheses:

If-then: “If the temperature in Fahrenheit is less than 60 degrees, significantly fewer students will study outside.”

Null: “If the temperature in Fahrenheit is less than 60 degrees, the same number of students will study outside as when it is more than 60 degrees.”

These hypotheses are plausible, as the temperatures are reasonably within the bounds of what is possible. The number of people in the quad is also easily observable. It is also not a phenomenon specific to only one person or at one time, but instead can explain a phenomenon for a broader group of people.

To complete this experiment, you pick the month of October to observe the quad. Every day (except on the days where it’s raining)from 3 to 4 PM, when most classes have released for the day, you observe how many people are on the quad. You measure how many people come  and how many leave. You also write down the temperature on the hour. 

After writing down all of your observations and putting them on a graph, you find that the most students study on the quad when it is 70 degrees outside, and that the number of students drops a lot once the temperature reaches 60 degrees or below. In this case, your research report would state that you accept or “failed to reject” your first hypothesis with your findings.

Experiment #2: The Cupcake Store (Forming a Simple Experiment)

Let’s say that you work at a bakery. You specialize in cupcakes, and you make only two colors of frosting: yellow and purple. You want to know what kind of customers are more likely to buy what kind of cupcake, so you set up an experiment. Your independent variable is the customer’s gender, and the dependent variable is the color of the frosting. What is an example of a hypothesis that might answer the question of this study?

Here’s what your hypotheses might look like: 

If-then: “If customers’ gender is female, then they will buy more yellow cupcakes than purple cupcakes.”

Null: “If customers’ gender is female, then they will be just as likely to buy purple cupcakes as yellow cupcakes.”

This is a pretty simple experiment! It passes the test of plausibility (there could easily be a difference), defined concepts (there’s nothing complicated about cupcakes!), observability (both color and gender can be easily observed), and general explanation ( this would potentially help you make better business decisions ).

Experiment #3: Backyard Bird Feeders (Integrating Multiple Variables and Rejecting the If-Then Hypothesis)

While watching your backyard bird feeder, you realized that different birds come on the days when you change the types of seeds. You decide that you want to see more cardinals in your backyard, so you decide to see what type of food they like the best and set up an experiment. 

However, one morning, you notice that, while some cardinals are present, blue jays are eating out of your backyard feeder filled with millet. You decide that, of all of the other birds, you would like to see the blue jays the least. This means you'll have more than one variable in your hypothesis. Your new hypotheses might look like this: 

If-then: “If sunflower seeds are placed in the bird feeders, then more cardinals will come than blue jays. If millet is placed in the bird feeders, then more blue jays will come than cardinals.”

Null: “If either sunflower seeds or millet are placed in the bird, equal numbers of cardinals and blue jays will come.”

Through simple observation, you actually find that cardinals come as often as blue jays when sunflower seeds or millet is in the bird feeder. In this case, you would reject your “if-then” hypothesis and “fail to reject” your null hypothesis . You cannot accept your first hypothesis, because it’s clearly not true. Instead you found that there was actually no relation between your different variables. Consequently, you would need to run more experiments with different variables to see if the new variables impact the results.

Experiment #4: In-Class Survey (Including an Alternative Hypothesis)

You’re about to give a speech in one of your classes about the importance of paying attention. You want to take this opportunity to test a hypothesis you’ve had for a while: 

If-then: If students sit in the first two rows of the classroom, then they will listen better than students who do not.

Null: If students sit in the first two rows of the classroom, then they will not listen better or worse than students who do not.

You give your speech and then ask your teacher if you can hand out a short survey to the class. On the survey, you’ve included questions about some of the topics you talked about. When you get back the results, you’re surprised to see that not only do the students in the first two rows not pay better attention, but they also scored worse than students in other parts of the classroom! Here, both your if-then and your null hypotheses are not representative of your findings. What do you do?

This is when you reject both your if-then and null hypotheses and instead create an alternative hypothesis . This type of hypothesis is used in the rare circumstance that neither of your hypotheses is able to capture your findings . Now you can use what you’ve learned to draft new hypotheses and test again! 

Key Takeaways: Hypothesis Writing

The more comfortable you become with writing hypotheses, the better they will become. The structure of hypotheses is flexible and may need to be changed depending on what topic you are studying. The most important thing to remember is the purpose of your hypothesis and the difference between the if-then and the null . From there, in forming your hypothesis, you should constantly be asking questions, making observations, doing secondary research, and considering your variables. After you have written your hypothesis, be sure to edit it so that it is plausible, clearly defined, observable, and helpful in explaining a general phenomenon.

Writing a hypothesis is something that everyone, from elementary school children competing in a science fair to professional scientists in a lab, needs to know how to do. Hypotheses are vital in experiments and in properly executing the scientific method . When done correctly, hypotheses will set up your studies for success and help you to understand the world a little better, one experiment at a time.

What’s Next?

If you’re studying for the science portion of the ACT, there’s definitely a lot you need to know. We’ve got the tools to help, though! Start by checking out our ultimate study guide for the ACT Science subject test. Once you read through that, be sure to download our recommended ACT Science practice tests , since they’re one of the most foolproof ways to improve your score. (And don’t forget to check out our expert guide book , too.)

If you love science and want to major in a scientific field, you should start preparing in high school . Here are the science classes you should take to set yourself up for success.

If you’re trying to think of science experiments you can do for class (or for a science fair!), here’s a list of 37 awesome science experiments you can do at home

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Ashley Sufflé Robinson has a Ph.D. in 19th Century English Literature. As a content writer for PrepScholar, Ashley is passionate about giving college-bound students the in-depth information they need to get into the school of their dreams.

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Hypothesis Testing | A Step-by-Step Guide with Easy Examples

Published on November 8, 2019 by Rebecca Bevans . Revised on June 22, 2023.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics . It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.

There are 5 main steps in hypothesis testing:

• State your research hypothesis as a null hypothesis and alternate hypothesis (H o ) and (H a  or H 1 ).
• Collect data in a way designed to test the hypothesis.
• Perform an appropriate statistical test .
• Decide whether to reject or fail to reject your null hypothesis.
• Present the findings in your results and discussion section.

Though the specific details might vary, the procedure you will use when testing a hypothesis will always follow some version of these steps.

Table of contents

Step 1: state your null and alternate hypothesis, step 2: collect data, step 3: perform a statistical test, step 4: decide whether to reject or fail to reject your null hypothesis, step 5: present your findings, other interesting articles, frequently asked questions about hypothesis testing.

After developing your initial research hypothesis (the prediction that you want to investigate), it is important to restate it as a null (H o ) and alternate (H a ) hypothesis so that you can test it mathematically.

The alternate hypothesis is usually your initial hypothesis that predicts a relationship between variables. The null hypothesis is a prediction of no relationship between the variables you are interested in.

• H 0 : Men are, on average, not taller than women. H a : Men are, on average, taller than women.

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For a statistical test to be valid , it is important to perform sampling and collect data in a way that is designed to test your hypothesis. If your data are not representative, then you cannot make statistical inferences about the population you are interested in.

There are a variety of statistical tests available, but they are all based on the comparison of within-group variance (how spread out the data is within a category) versus between-group variance (how different the categories are from one another).

If the between-group variance is large enough that there is little or no overlap between groups, then your statistical test will reflect that by showing a low p -value . This means it is unlikely that the differences between these groups came about by chance.

Alternatively, if there is high within-group variance and low between-group variance, then your statistical test will reflect that with a high p -value. This means it is likely that any difference you measure between groups is due to chance.

Your choice of statistical test will be based on the type of variables and the level of measurement of your collected data .

• an estimate of the difference in average height between the two groups.
• a p -value showing how likely you are to see this difference if the null hypothesis of no difference is true.

Based on the outcome of your statistical test, you will have to decide whether to reject or fail to reject your null hypothesis.

In most cases you will use the p -value generated by your statistical test to guide your decision. And in most cases, your predetermined level of significance for rejecting the null hypothesis will be 0.05 – that is, when there is a less than 5% chance that you would see these results if the null hypothesis were true.

In some cases, researchers choose a more conservative level of significance, such as 0.01 (1%). This minimizes the risk of incorrectly rejecting the null hypothesis ( Type I error ).

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The results of hypothesis testing will be presented in the results and discussion sections of your research paper , dissertation or thesis .

In the results section you should give a brief summary of the data and a summary of the results of your statistical test (for example, the estimated difference between group means and associated p -value). In the discussion , you can discuss whether your initial hypothesis was supported by your results or not.

In the formal language of hypothesis testing, we talk about rejecting or failing to reject the null hypothesis. You will probably be asked to do this in your statistics assignments.

However, when presenting research results in academic papers we rarely talk this way. Instead, we go back to our alternate hypothesis (in this case, the hypothesis that men are on average taller than women) and state whether the result of our test did or did not support the alternate hypothesis.

If your null hypothesis was rejected, this result is interpreted as “supported the alternate hypothesis.”

These are superficial differences; you can see that they mean the same thing.

You might notice that we don’t say that we reject or fail to reject the alternate hypothesis . This is because hypothesis testing is not designed to prove or disprove anything. It is only designed to test whether a pattern we measure could have arisen spuriously, or by chance.

If we reject the null hypothesis based on our research (i.e., we find that it is unlikely that the pattern arose by chance), then we can say our test lends support to our hypothesis . But if the pattern does not pass our decision rule, meaning that it could have arisen by chance, then we say the test is inconsistent with our hypothesis .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Descriptive statistics
• Measures of central tendency
• Correlation coefficient

Methodology

• Cluster sampling
• Stratified sampling
• Types of interviews
• Cohort study
• Thematic analysis

Research bias

• Implicit bias
• Cognitive bias
• Survivorship bias
• Availability heuristic
• Nonresponse bias
• Regression to the mean

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

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100 Hypothesis Examples Across Various Academic Fields

A hypothesis is a statement or proposition that is made for the purpose of testing through empirical research. It represents an educated guess or prediction that can be tested through observation and experimentation. A hypothesis is often formulated using a logical construct of "if-then" statements, allowing researchers to set up experiments to determine its validity. It serves as the foundation of a scientific inquiry, providing a clear focus and direction for the study. In essence, a hypothesis is a provisional answer to a research question , which is then subjected to rigorous testing to determine its accuracy.

In this blog post, we'll explore 100 different hypothesis examples, showing you how these simple statements set the stage for discovery in various academic fields. From the mysteries of chemical reactions to the complexities of human behavior, hypotheses are used to kickstart research in numerous disciplines. Whether you're new to the world of academia or just curious about how ideas are tested, these examples will offer insight into the fundamental role hypotheses play in learning and exploration.

• If a plant is given more sunlight, then it will grow faster.
• If an animal's environment is altered, then its behavior will change.
• If a cell is exposed to a toxin, then its function will be impaired.
• If a species is introduced to a new ecosystem, then it may become invasive.
• If an antibiotic is applied to a bacterial culture, then growth will be inhibited.
• If a gene is mutated, then the corresponding protein may become nonfunctional.
• If a pond's water temperature rises, then the algae population will increase.
• If a bird species' habitat is destroyed, then its population will decrease.
• If a mammal is given a high-fat diet, then its cholesterol levels will rise.
• If human stem cells are treated with specific factors, then they will differentiate into targeted cell types.
• If the concentration of a reactant is increased, then the rate of reaction will increase.
• If a metal is placed in a solution of a salt of a less reactive metal, then a displacement reaction will occur.
• If a solution's pH is lowered, then the concentration of hydrogen ions will increase.
• If a gas is cooled at constant pressure, then its volume will decrease according to Charles's law.
• If an endothermic reaction is heated, then the equilibrium position will shift to favor the products.
• If an enzyme is added to a reaction, then the reaction rate will increase due to the lower activation energy.
• If the pressure on a gas is increased at constant temperature, then the volume will decrease according to Boyle's law.
• If a non-polar molecule is added to water, then it will not dissolve due to water's polarity.
• If a piece of litmus paper is placed in a basic solution, then the color of the paper will turn blue.
• If an electric current is passed through a salt solution, then the solution will undergo electrolysis and break down into its components.

Computer science

• If a new algorithm is applied to a sorting problem, then the computational complexity will decrease.
• If multi-factor authentication is implemented, then the security of a system will increase.
• If a machine learning model is trained with more diverse data, then its predictive accuracy will improve.
• If the bandwidth of a network is increased, then the data transmission rate will be faster.
• If a user interface is redesigned following usability guidelines, then user satisfaction and efficiency will increase.
• If a specific optimization technique is applied to a database query, then the retrieval time will be reduced.
• If a new cooling system is used in a data center, then energy consumption will decrease.
• If parallel processing is implemented in a computational task, then the processing time will be reduced.
• If a software development team adopts Agile methodologies, then the project delivery time will be shortened.
• If a more advanced error correction code is used in data transmission, then the error rate will decrease.
• If the interest rate is lowered, then consumer spending will increase.
• If the minimum wage is raised, then unemployment may increase among low-skilled workers.
• If government spending is increased, then the Gross Domestic Product (GDP) may grow.
• If taxes on luxury goods are raised, then consumption of those goods may decrease.
• If a country's currency is devalued, then its exports will become more competitive.
• If inflation is high, then the central bank may increase interest rates to control it.
• If consumer confidence is high, then spending in the economy will likely increase.
• If barriers to entry in a market are reduced, then competition will likely increase.
• If a firm engages in monopolistic practices, then consumer welfare may decrease.
• If unemployment benefits are extended, then the unemployment rate may be temporarily affected.
• If class sizes are reduced, then individual student performance may improve.
• If teachers receive ongoing professional development, then teaching quality will increase.
• If schools implement a comprehensive literacy program, then reading levels among students will rise.
• If parents are actively involved in their children's education, then students' academic achievement may increase.
• If schools provide more access to extracurricular activities, then student engagement and retention may improve.
• If educational technology is integrated into the classroom, then learning outcomes may enhance.
• If a school adopts a zero-tolerance policy on bullying, then the incidence of bullying will decrease.
• If schools provide nutritious meals, then student concentration and performance may improve.
• If a curriculum is designed to include diverse cultural perspectives, then student understanding of different cultures will increase.
• If schools implement individualized learning plans, then students with special needs will achieve better educational outcomes.

Environmental science

• If deforestation rates continue to rise, then biodiversity in the area will decrease.
• If carbon dioxide emissions are reduced, then the rate of global warming may decrease.
• If a water body is polluted with nutrients, then algal blooms may occur, leading to eutrophication.
• If renewable energy sources are used more extensively, then dependency on fossil fuels will decrease.
• If urban areas implement green spaces, then the urban heat island effect may be reduced.
• If protective measures are not implemented, then endangered species may become extinct.
• If waste recycling practices are increased, then landfill usage and waste pollution may decrease.
• If air quality regulations are enforced, then respiratory health issues in the population may decrease.
• If soil erosion control measures are not implemented, then agricultural land fertility may decrease.
• If ocean temperatures continue to rise, then coral reefs may experience more frequent bleaching events.
• If a new chemotherapy drug is administered to cancer patients, then tumor size will decrease more effectively.
• If a specific exercise regimen is followed by osteoarthritis patients, then joint mobility will improve.
• If a population is exposed to higher levels of air pollution, then respiratory diseases such as asthma will increase.
• If a novel surgical technique is utilized in cardiac surgery, then patient recovery times will be shortened.
• If a targeted screening program is implemented for a specific genetic disorder, then early detection and intervention rates will increase.
• If a community's water supply is fortified with fluoride, then dental cavity rates in children will decrease.
• If an improved vaccination schedule is followed in a pediatric population, then the incidence of preventable childhood diseases will decline.
• If nutritional supplements are provided to malnourished individuals, then general health and immune function will improve.
• If stricter infection control protocols are implemented in hospitals, then the rate of hospital-acquired infections will decrease.
• If organ transplant recipients are given a new immunosuppressant drug, then organ rejection rates will decrease.
• If a person is exposed to violent media, then their aggression levels may increase.
• If a child is given positive reinforcement, then desired behaviors will be more likely to be repeated.
• If an individual suffers from anxiety, then their performance on tasks under pressure may decrease.
• If a patient is treated with cognitive-behavioral therapy, then symptoms of depression may reduce.
• If a person lacks sleep, then their cognitive functions and decision-making abilities will decline.
• If an individual's self-esteem is increased, then their overall life satisfaction may improve.
• If a person is exposed to a traumatic event, then they may develop symptoms of PTSD.
• If social support is provided to an individual, then their ability to cope with stress will improve.
• If a group works collaboratively, then they may exhibit improved problem-solving abilities.
• If an individual is given autonomy in their work, then their job satisfaction and motivation will increase.
• If the velocity of an object is increased, then the kinetic energy will also increase.
• If the temperature of a gas is increased at constant pressure, then the volume will increase.
• If the mass of an object is doubled, then the gravitational force it exerts will also double.
• If the frequency of a wave is increased, then the energy it carries will increase.
• If a magnet's distance from a metal object is decreased, then the magnetic force will increase.
• If the angle of incidence equals the angle of reflection, then the law of reflection holds true.
• If the resistance in an electrical circuit is increased, then the current will decrease.
• If the force applied to a spring is doubled, then the extension of the spring will also double.
• If a mirror is concave, then it will focus parallel rays to a point.
• If a body is in uniform circular motion, then the net force toward the center is providing the centripetal acceleration.
• If educational opportunities are equally distributed in a society, then social mobility will increase.
• If community policing strategies are implemented, then trust between law enforcement and the community may improve.
• If social media usage increases among teenagers, then face-to-face social interaction may decrease.
• If gender wage gap policies are enforced, then disparities in earnings between men and women will decrease.
• If a society emphasizes individualistic values, then community engagement and collective responsibility may decline.
• If affordable housing initiatives are implemented in urban areas, then homelessness rates may decrease.
• If a minority group is represented in media, then stereotypes and prejudices toward that group may decrease.
• If a culture promotes work-life balance, then overall life satisfaction among its citizens may increase.
• If increased funding is provided to community centers in underserved neighborhoods, then social cohesion and community engagement may improve.
• If legislation is passed to protect the rights of LGBTQ+ individuals, then discrimination and stigma may decrease in society.

In the exploration of various academic disciplines, hypotheses play a crucial role as foundational statements that guide research and inquiry. From understanding complex biological processes to navigating the nuances of human behavior in sociology, hypotheses serve as testable predictions that shape the direction of scientific investigation. The examples provided across the fields of medicine, computer science, sociology, and education illustrate the diverse applications and importance of hypotheses in shaping our understanding of the world. Whether improving medical treatments, enhancing technological systems, fostering social equality, or elevating educational practices, hypotheses remain central to scientific progress and societal advancement. By formulating clear and measurable hypotheses, researchers can continue to unravel complex phenomena, contribute to their fields, and ultimately enrich human knowledge and well-being.

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How to Write a Hypothesis With Examples and Explanations

• Icon Calendar 18 May 2024
• Icon Page 1590 words
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A hypothesis refers to a statement that predicts the findings of a research study. Basically, researchers develop propositions to provide tentative answers to research questions that address different aspects of the research question. In this case, a scholar must use existing theories and knowledge to create an assumption. Besides, a researcher focuses on testing supposed claims through different methods, like experiments, observations, and statistical analysis of the data. In practice, the findings from a study can either support or refute a hypothesis. Then, when writing a suggestion, scholars should conduct adequate research on the topic, brainstorm for ideas, draft a hypothesis, revise a draft supposition, and write a final claim in simple language. Also, these steps lead to the development of accurate and precise propositions that identify relationships between independent and dependent variables. In practice, one should rely on a cause and effect theory when developing a hypothesis.

General Aspects of Writing a Hypothesis

A hypothesis suggests a sentence as a statement that gives a prediction about the findings of a research study. Basically, researchers make a hypothesis, which acts as a tentative answer to the research question. In this case, a proposition lacks scientific or scholarly proof. Then, a reasonable hypothesis must address different aspects of the research question. In turn, researchers must base a proposition on existing theories and knowledge. Besides, it has to be testable through various methods, like experiments, observations, and statistical analysis. In practice, the findings from a study can either support or refute a working hypothesis. Therefore, a hypothesis refers to a statement that tries to predict the results of a survey.

Independent and Dependent Variables

A hypothesis in some studies must contain independent and dependent variables. For example. experimental and correlational research examines relationships between two or more variables. In turn, independent variables refer to factors that researchers can control or change. Besides, a dependent variable refers to factors that scholars observe or measure. Then, a null hypothesis of experimental and correlational studies must predict relationships between dependent and independent variables. Moreover, such predictions should not be guesses but should contain evidence from research studies.

Types of a Hypothesis

There are different types of hypotheses that researchers can develop in their studies. In this case, the following are the common types of hypotheses:

• A simple hypothesis refers to predictions of relationships between independent and dependent variables.
• A complex hypothesis predicts relationships between two or more independent and dependent variables.
• An empirical hypothesis is a working prediction that exists when a researcher tests a theory by using observations and experiments. Basically, this type of hypothesis goes through some trial and error methods to obtain the necessary findings. In some instances, researchers may change some variables around other variables.  
• A null hypothesis , denoted as H 0 , exists when a researcher believes that a relationship does not exist between independent and dependent variables. Basically, this hypothesis may exist when a researcher lacks adequate information to make a scientific prediction. Besides, inferences made from the findings attempt to disapprove or discredit a null hypothesis.  
• An alternative hypothesis , denoted as H 1 , attempts to disapprove a null hypothesis. In this case, researchers attempt to discover or affirm an alternative proposition. 
• A logical hypothesis refers to a proposed explanation of a concept that contains limited evidence. In practice, investigators intend to turn a reasonable assumption into an empirical claim. Also, researchers put theories or postulate them to the test.
• A statistical hypothesis is a claim related to studies that examine a section of the population. In this case, researchers identify a sample population and study their behaviors related to the research question. 

Crafting a Hypothesis

Researchers should focus on developing reasonable hypotheses for their studies. For example, one should consider different factors that relate to existing studies or theories. In this case, some predictions should pertain to research data and provide tentative answers to research questions. Hence, the following are the essential steps that a researcher should consider when developing a hypothesis.

Step 1. Researching

The first step in developing a hypothesis is to research and gather details related to the intended topic. Basically, researching allows a scholar to gain more knowledge concerning issues and factors and how variables change. Besides, this step will enable researchers to become familiar with the expected results. As a result, it influences a relevant hypothesis’s development.

Step 2. Asking Questions

A researcher should develop research questions before developing a hypothesis. For instance, investigators should create scientific questions that relate to the study and identified variables. In this case, brainstorming enhances the ability to determine relationships between independent and dependent variables. Basically, successful scholars remain focused on one cause and effect theory to ensure that they develop accurate ideas for a hypothesis. Therefore, the second step in developing a proposition is to brainstorm questions that reveal the relationship between independent and dependent variables. 

Step 3. Use Clear Language

Scholars should use simple and clear language when developing a hypothesis for a study. For instance, one should draft concise predictions that answer developed research questions. In practice, one should write a hypothesis in a form that proposes that an action leads to a specific result. Moreover, a researcher should not state a supposition as a question but as an affirmative statement that predicts outcomes from a particular course of action. Therefore, the third step in developing a hypothesis involves selecting a simple language for drafting scientific predictions. 

Step 4. Revising a Hypothesis

A scholar should revise a draft hypothesis to ensure that it makes a testable thesis through research and experimentation. For instance, a researcher should review a prediction to ensure that it captures relationships between at least two variables. Hence, a scholar must revise a drafted hypothesis to ensure that it captures a testable relationship between independent and dependent variables.     

Examples of a Hypothesis

1. sociology.

• Research question – How does divorce affect sociological development among young children?
• H 0 – Challenges that lead to divorce hurt young children’s social development, which affects their ability to interact with other people. 
• H 1 – Most children manage to cope with domestic challenges that lead to divorce, enabling them to realize healthy sociological development.
• Research question – How did tenebrism influence baroque art during the 16 th and 17 th centuries?
• H 0 – The origin of tenebrism had a positive impact on the dynamic appearance of baroque art.
• H 1 – Baroque art emerged as a unique art that did not have any form of external influence.

3. Geography

• Research question – To what extent does geological activity affect the Earth?
• H 0 – The movement of tectonic plates beneath the Earth’s surface results in volcanic eruptions and faults that lead to mountains and lift valleys.  
• H 1 – Mountains and valleys are natural features with little connection with geological activities like the movement of tectonic plates beneath the Earth’s surface.

4. Philosophy Hypothesis

• Research question – Do animals have rights and welfare in society?
• H 0 – Wild and domestic animals are living creatures with a right to care and protection by humans.
• H 1 – Wild and domestic animals are subordinate to humans, which implies that they do not have a right to care and protection.  
• Research question – Does the consumption of genetically modified plants cause health complications in humans?
• H 0 – Genetically modified foods are safe for human consumption and do not pose any possible health risks.
• H 1 – Genetically modified foods interfere with healthy cell development, which leads to health complications.

4. Indigenous Studies

• Research question – What role does culture play among indigenous communities?
• H 0 – Cultural practices among Aboriginals promote their identity and contribute to the members’ overall well-being.
• H 1 – cultural practices among Aboriginals do not significantly contribute to the quality of their lives.
• Research question – Does fascism exist in the twenty-first century?
• H 0 – The established forms of democracy in the twenty-first century do not allow political leaders to implement all the fascism elements.
• H 1 – Some political leaders in the twenty-first century adopt radical policies that promote the existence of fascism.
• Research question – Do neutrons have mass?
• H 0 – Neutrons are small particles that have masses.
• H 1 – Neutrons are small particles whose weight remains insignificant.

7. Health Studies

• Research question – How do evidence-based treatment approaches enhance the quality of the treatments?
• H 0 – Evidence-based treatment methods allow doctors to gather adequate and accurate information about the patient, which helps tailor treatment and care approaches to meet the patient’s needs.
• H 1 – Evidence-based approaches do not enhance the quality of the treatments since they lead to inconsistency in the care and medications given to a patient.

8. Environmental Studies

• Research question – To what extent do human activities contribute to global warming?
• H 0 – Most human activities release greenhouse gases into the atmosphere, which results in the rise of average temperatures.
• H 1 – Most human activities release insignificant amounts of greenhouse gases into the atmosphere, contributing to global warming.

Summing Up on How to Write a Good Scientific Hypothesis in a Research Paper

A hypothesis gives a prediction about the findings of a research study. Basically, researchers develop hypotheses to provide a tentative answer to research questions. In turn, some of the factors that one must consider when writing a hypothesis include:

• conduct adequate research on the topic;
• brainstorm for ideas;
• draft a hypothesis;
• revise a draft proposition;
• write a final hypothesis in simple language.

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How to Write a Hypothesis? [Tips with Examples]

Click here if you have ever found yourself in the position of having to wrestle with the development of a hypothesis for your research paper. As an expert writer, I have seen that this is where most students begin to sweat. It is a potpourri of theory and practice, hence rather intimidating. But not to worry because I have got your back. This guide is a pool of tips and tricks for writing a hypothesis to set the stage for compelling research.

What is a Hypothesis?

A hypothesis is a tentative statement, usually in the form of an educated guess, that provides a probable explanation for something either a phenomenon or a relationship between variables. This will, therefore, form a basis for conducting experiments and research studies, hence laying down the course of your investigation and mainly laying the ground for your conclusion.

A good hypothesis should be:

Specific and clear

Testable and falsifiable

Based upon existing knowledge

Logically consistent

Types of Hypothesis

There are different kinds of hypotheses used in research, all of which serve different purposes depending on the nature of the study. Here are eight common types:

1. The null hypothesis (H0):  asserts that there is no effect or relationship between variables. This forms a baseline for comparison. Example: "There is no difference in test scores for students who study music and for those who do not."

2. Alternative Hypothesis (H1): The hypothesis that postulates some effect or relationship between variables; it is, therefore, the opposite of the null hypothesis. For instance, "Students who study with music have different test scores than those who study in silence."

3. Simple Hypothesis: The hypothesis that states a relationship between two variables: one independent and one dependent. For example, "More sunlight increases plant growth."

4. Complex Hypothesis: This hypothesis involves the relationship of more than one variable. For example, "More sunlight and water increase plant growth."

5. Directional Hypothesis: The hypothesis which specifies the direction of the effect between variables. For instance, "Students who study with music will have higher test scores than students who study in silence."

6. Non-Directional Hypothesis: This is a hypothesis used where the relationship is indicated, but the direction is not specified. For example, "There is a difference in test scores between students who study with music and those who study in silence."

7. Associative Hypothesis: This hypothesis merely states that the change in one variable is associated with a change in another. It does not indicate cause and effect. For example: "There is a relationship between study habits and academic performance."

8. Causal Hypothesis: This hypothesis states that one variable causes a change in another. For example: "Increased study time results in higher test scores."

Understanding such types of hypotheses will help in the selection of the correct hypothesis for your research and in making your analysis clear and effective.

5 Steps to Write a Good Hypothesis [With Examples]

An excellent hypothesis provides a backbone to any scientific research. Leave some help behind in writing one? Follow this easy guide:

Step 1: Ask a Question

First, you must understand what your research question is. Suppose you want to carry out an experiment on plant growth. Your question can be, "How does sunlight affect plant growth?"

Use WPS AI to help when you get stuck. Feed it a topic, and it will come up with related questions to ask.

Step 2: Do Preliminary Research

Do some research to see what's already known about your topic. That way, you can build upon existing knowledge.

Research information in journals, books and credible websites. Then summarize what you read. This will help you formulate your hypothesis.

Step 3: Define Variables

Identify your variables:

Independent Variable: What you manipulate. For example, the amount of sun.

Dependent Variable: What you measure. For example, plant growth rate.

Clearly defining these makes your hypothesis specific and testable.

Step 4: State Your Hypothesis

State your question in the form of a hypothesis. Here are some examples:

If  then: "If plants receive more sunlight, then they will grow faster."

Comparative statements: "Plants receiving more sunlight grow faster than plants receiving less."

Correlation statements: "There is positive correlation between sunlight and plant growth." This kind of pattern makes your hypothesis easy to test.

Step 5: Refine Your Hypothesis

Revise your hypothesis to be clear and specific, and elicit feedback to improve it.

You will also need a null hypothesis, which says that there is no effect or relationship between variables. An example would be, "Sunlight has no effect on the growth of plants."

With these steps, you are now bound to come up with a testable hypothesis. WPS AI can help you in this process more efficiently.

Characteristics of a Good Hypothesis

A good hypothesis is seen as the backbone of doing effective research. Following are some key characteristics that define a good hypothesis:

A good hypothesis has to be testable either by experimentation or observation. The hypothesis should clearly predict what can be measured or observed. For example, "If it receives more sunlight, the plant will grow taller" is a testable hypothesis since it states what can be measured.

Falsifiable

A hypothesis has to be falsifiable: it should be able to prove it wrong. This feature is important because it accommodates testing in science. For example, the statement "All swans are white" is falsifiable since it just takes one black swan to disprove the claim.

A good hypothesis should be grounded in current knowledge and should be properly reasoned. It should be broad or reasonable within existing knowledge. For example, "Increasing the amount of sunlight will boost plant growth" makes sense, in that it tallies with generally known facts about photosynthesis.

Specific and Clear

What is needed is clarity and specificity. A hypothesis has to be brief, yet free from ambiguity. For instance, "Increased sunlight leads to taller plants" is clear and specific whereas "Sunlight affects plants" is too vague.

Built upon Prior Knowledge

A good hypothesis is informed by prior research and existing theories. The available knowledge enlightens it to build on what is known to find new relationships or effects. For example, "Given photosynthesis requires sunlight, increasing sunlight will enhance plant growth" is informed by available scientific understanding.

Ethical Considerations

Finally, a good hypothesis needs to consider the ethics involved. The research should not bring damage to participants or the environment. For instance, "How the new drug will affect a human when tested without testing it on animals" may present an ethical concern.

Checklist for Reviewing Your Hypothesis

To be certain that your hypothesis has the following characteristics, use this checklist to review your hypothesis:

1. Is the hypothesis testable through experimentation or observation?

2. Can the hypothesis be proven false?

3. Is the hypothesis logically deduced from known facts?

4. Is your hypothesis clear and specific?

5. Does your hypothesis relate to previous research or theories?

6. Will there be any ethical issues with the proposed research?

7. Are your independent and dependent variables well defined?

8. Is your hypothesis concise and ambiguity free?

9. Did you get feedback to help in refining your hypothesis?

10. Does your hypothesis contain a null hypothesis for comparison?

By making sure that your hypothesis has these qualities, you are much more likely to set yourself on the course of higher-quality research and larger impacts. WPS AI can help fine-tune a hypothesis to ensure it is well-structured and clear.

Using WPS to Perfect your Hypothesis

Drafting a good hypothesis is the real inception of any research project. WPS AI, with its advanced language functions, can very strongly improve this stage of your study. Here's how WPS AI can help you perfect your hypothesis:

Check Grammar and Syntax

Grammar and punctuation errors can make your hypothesis weak. WPS AI checks and corrects this with the assurance that your hypothesis is as clear as possible and professional in its presentation. For example, when your hypothesis is written, "If the temperature increases then plant growth will increases", WPS AI can correct it to "If the temperature increases, then plant growth will increase."

Rewrite Your Hypothesis for Clarity

There needs to be a clear hypothesis. WPS AI can suggest ways to reword your hypothesis so that it makes sense. If your original hypothesis is, "More sunlight will result in more significant plant growth due to photosynthesis," WPS AI can suggest, "Increased sunlight will lead to greater plant growth through enhanced photosynthesis."

Automatic Content Expansion

Sometimes, your hypothesis or the related paragraphs may require more detail. WPS AI's [Continue Writing] feature can help enlarge the content. For example, after having written, "This study will examine the effects of sunlight on plant growth", using [Continue Writing] it can enlarge it to, "This research paper is going to study how sunlight affects the growth of plants by measuring their height and their health under different amounts of sunlight over a period of six weeks."

WPS AI is a great tool that can help you in drafting a good hypothesis for your research. It will help you check grammar, syntax, clarity, and completeness. Using WPS AI , you will be assured that the results of your hypothesis will be well-written and clear to understand.

What is the difference between a hypothesis and a theory?

The hypothesis is one single testable prediction regarding some phenomenon. The theory is an explanation for some part of the natural world which is well-substantiated by a body of evidence, together with multiple hypotheses.

What do I do if my hypothesis isn't supported by my data?

If your results turn out not to support your hypothesis, analyze the data again to see why your result rejects your hypothesis. Do not manipulate the observations or experiment so that it leads to your hypothesis.

Can there be more than one hypothesis in a research study?

Yes, there may be more than one hypothesis, especially when one research study is examining several interrelated phenomena or variables. Each hypothesis has to be separately and clearly stated and tested.

Correct formulation of a strong, testable hypothesis is one of the most critical steps in the application of the scientific method and within academic research. The steps provided in this article will help you write a hypothesis that is clear, specific, and based on available knowledge. Give the tools and tips a try to elevate your academic writing and kick your research up a notch.

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3 Point Thesis Statement

Ai generator.

A 3-point thesis statement is a concise yet potent tool that outlines the main arguments of your paper. By presenting three key points, it guides readers through your central ideas and supports your position. In this guide, we’ll explore how to create compelling 3-point thesis statements , along with valuable tips to ensure clarity, coherence, and persuasive strength in your academic writing.

Definition of a 3 Point Thesis Statement

A 3-point thesis statement is a succinct and focused sentence that outlines the main arguments or points you intend to address in your paper. It serves as a roadmap for your readers, indicating the core topics or themes you’ll explore while presenting your stance or perspective on a particular issue.

Example of a 3 Point Thesis Statement

Topic: The Impact of Climate Change on Biodiversity

Thesis Statement: “The accelerating effects of climate change threaten global biodiversity through temperature shifts, habitat degradation, and altered migration patterns.”

In this example, the 3-point thesis statement clearly presents the three main points that will be discussed in the paper: temperature shifts, habitat degradation, and altered migration patterns. These points provide a structured framework for the upcoming argumentative analysis.

100 Three Point Thesis Statement Examples

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A 3-point thesis statement succinctly outlines central arguments, providing a roadmap for focused discussions. Below are 100 examples spanning various subjects, each followed by a brief 60-word description:

• Cyberbullying Effects on Adolescents Cyberbullying adversely impacts adolescents’ mental health, self-esteem, and academic performance. This thesis addresses the detrimental effects of cyberbullying on adolescents’ psychological well-being, academic achievement, and self-perception.
• Renewable Energy Solutions Renewable energy systems contribute to sustainability through reduced emissions, resource conservation, and energy independence. This thesis explores the multifaceted benefits of renewable energy, including its role in combating climate change, conserving resources, and fostering energy autonomy.
• Gender Stereotypes in Media Media perpetuates gender stereotypes through representation, roles, and normalized behaviors. Focusing on media’s influence, this thesis analyzes how gender stereotypes are reinforced through portrayal, societal roles, and the reinforcement of normalized behaviors.
• The Impact of Social Media on Politics Social media shapes political discourse by influencing awareness, engagement, and public opinion. Examining the intersection of technology and politics, this thesis delves into how social media platforms shape political discussions by impacting awareness, engagement, and public sentiment.
• Cultural Diversity in Education Incorporating diverse perspectives in education enhances critical thinking, empathy, and global understanding. This thesis underscores the significance of integrating diverse viewpoints into educational curricula, fostering skills such as critical thinking, empathy, and cross-cultural awareness.
• Impact of Artificial Intelligence on Job Market Artificial intelligence transforms employment landscapes by reshaping job roles, skill demands, and the need for adaptability. Investigating AI’s influence on jobs, this thesis explores how automation shifts job responsibilities, necessitates new skills, and emphasizes the importance of adaptability.
• Effects of Social Media on Teenage Body Image Social media shapes teenage body image through comparisons, idealized representations, and societal beauty standards. This thesis delves into how social media influences teenagers’ perceptions of body image by promoting comparisons, unrealistic ideals, and cultural beauty norms.
• Ethical Implications of Genetic Engineering Genetic engineering raises ethical concerns over altering organisms, patenting life forms, and unforeseen ecological consequences. Analyzing the ethical dimensions, this thesis examines debates surrounding genetic modification, including ethical dilemmas, intellectual property, and environmental risks.
• Education’s Role in Addressing Poverty Education is a catalyst for poverty alleviation by fostering skills, knowledge, and socio-economic mobility. This thesis emphasizes education’s pivotal role in breaking the cycle of poverty through skill development, knowledge acquisition, and improved economic prospects.
• Media’s Influence on Political Polarization Media exacerbates political polarization by disseminating biased information, echo chambers, and fostering extremism. Investigating media’s role, this thesis explores how biased reporting, echo chambers, and extremist content contribute to the widening political divide.
• Environmental Conservation and Economic Growth Environmental conservation and economic growth can coexist through sustainable practices, green technologies, and eco-tourism. This thesis examines the compatibility of preserving the environment and promoting economic development by emphasizing sustainable practices, technology, and eco-friendly industries.
• Impacts of Social Media on Interpersonal Relationships Social media alters interpersonal relationships by affecting communication dynamics, intimacy, and personal interactions. Exploring technology’s influence on relationships, this thesis analyzes how social media shapes communication patterns, intimacy levels, and face-to-face interactions.
• Globalization’s Effects on Cultural Diversity Globalization both enriches and endangers cultural diversity through cultural exchange, homogenization, and cultural appropriation. This thesis examines globalization’s dual effects, including the enrichment of cultural exchange and the challenges of cultural homogenization and appropriation.
• The Role of Education in Promoting Environmental Stewardship Education fosters environmental stewardship by instilling awareness, responsibility, and sustainable behaviors. Addressing the intersection of education and the environment, this thesis underscores how education cultivates environmental consciousness, accountability, and sustainable practices.
• Artificial Intelligence and Healthcare Diagnostics Artificial intelligence revolutionizes healthcare diagnostics through precise analysis, early detection, and improved patient outcomes. Exploring AI’s impact on healthcare, this thesis assesses how AI enhances medical diagnoses by providing accurate analyses, detecting conditions earlier, and optimizing patient care.
• Media’s Influence on Consumer Behavior Media shapes consumer behavior by creating desires, trends, and influencing purchasing decisions. Focusing on media’s sway, this thesis examines how advertising and media content drive consumer desires, shape trends, and impact buying choices.
• Education’s Role in Fostering Tolerance and Inclusion Education cultivates tolerance and inclusion by promoting empathy, understanding, and dismantling stereotypes. This thesis highlights how education plays a vital role in creating inclusive societies through empathy-building, stereotype deconstruction, and fostering understanding.
• Ethical Considerations in Artificial Intelligence Development Ethical concerns surround AI development due to bias, privacy invasion, and the potential for autonomous decision-making. Addressing the ethical dimensions, this thesis evaluates the moral implications associated with AI development, including issues of bias, privacy, and decision-making autonomy.
• Media’s Influence on Political Engagement Media influences political engagement by shaping public opinion, mobilizing activism, and framing political narratives. Examining media’s role in politics, this thesis analyzes how media outlets shape public perceptions, drive activism, and contribute to the framing of political issues.
• Sustainable Agriculture and Food Security Sustainable agriculture ensures food security through ecological practices, crop diversity, and responsible resource management. Investigating the relationship between agriculture and food security, this thesis explores how sustainable practices, diverse crops, and resource conservation bolster global food supplies
• Technology’s Impact on Education Technology transforms education through online learning, personalized instruction, and innovative teaching methods. Examining the intersection of technology and education, this thesis assesses how digital tools reshape learning environments, enhance personalization, and revolutionize teaching techniques.
• Effects of Social Media on Mental Health Social media affects mental health through comparison, cyberbullying, and the pressure of maintaining online personas. Investigating mental health implications, this thesis explores how social media contributes to anxiety, depression, and other mental health challenges through comparison, bullying, and curated online identities.
• The Role of Literature in Shaping Societal Norms Literature shapes societal norms by reflecting culture, challenging conventions, and fostering critical discourse. Examining literature’s impact, this thesis analyzes how literary works influence societal values, prompt reflection, and challenge established norms.
• Online Privacy and Personal Data Protection Online privacy hinges on protecting personal data from breaches, surveillance, and unauthorized use. Addressing digital security, this thesis explores the complexities of safeguarding personal information from cyber threats, unauthorized access, and surveillance.
• Media’s Role in Shaping Historical Narratives Media influences historical narratives by framing events, shaping memory, and emphasizing certain perspectives. Focusing on media’s historical impact, this thesis examines how media narratives influence collective memory, historical understanding, and the framing of significant events.
• Economic Inequality and Access to Education Economic inequality affects education access through disparities in resources, quality, and opportunities. Addressing the connection between wealth disparity and education, this thesis explores how economic inequalities impact access to quality education and opportunities.
• Influence of Social Media on Democracy Social media affects democracy by shaping political discourse, enabling citizen participation, and disseminating information. Examining the intersection of technology and politics, this thesis assesses how social media platforms influence democratic processes, political engagement, and information dissemination.
• Effects of Climate Change on Coastal Communities Climate change poses risks to coastal communities through rising sea levels, extreme weather events, and erosion. Investigating climate impacts, this thesis explores how rising temperatures and changing weather patterns threaten coastal areas with sea-level rise, storms, and erosion.
• The Role of Art in Cultural Preservation Art contributes to cultural preservation by conveying heritage, identity, and historical narratives. Focusing on artistic expression, this thesis examines how art serves as a vessel for cultural memory, preservation of traditions, and the portrayal of historical stories.
• Media’s Influence on Beauty Standards Media shapes beauty standards through idealized images, promoting unrealistic ideals, and setting cultural norms. Analyzing media’s role in shaping perceptions of beauty, this thesis explores how media images influence cultural definitions of attractiveness and self-worth.
• The Impact of Artificial Intelligence on Ethics Artificial intelligence raises ethical concerns related to bias, decision-making, and the potential for autonomous systems. Addressing the ethical dimensions of AI, this thesis evaluates how machine learning technologies introduce ethical dilemmas in areas such as bias, decision-making, and autonomy.
• Literature’s Exploration of Social Injustice Literature critiques social injustice by depicting marginalized experiences, advocating for change, and prompting reflection. This thesis analyzes how literary works shed light on societal inequalities, advocate for marginalized voices, and inspire social change.
• Effects of Video Games on Cognitive Development Video games impact cognitive development through problem-solving, spatial awareness, and enhanced multitasking skills. Examining the influence of gaming, this thesis explores how interactive digital entertainment contributes to cognitive skill development in areas such as problem-solving and multitasking.
• The Role of Education in Gender Equality Education empowers gender equality by challenging stereotypes, promoting opportunities, and fostering inclusive mindsets. Addressing the intersection of education and gender, this thesis emphasizes how educational systems contribute to dismantling gender stereotypes, increasing opportunities, and promoting gender inclusivity.
• Effects of Social Media on News Consumption Social media shapes news consumption patterns through personalized feeds, viral content, and the spread of misinformation. Investigating media’s impact on news consumption, this thesis examines how social media algorithms, viral content, and misinformation affect the way individuals access and interpret news.
• Urbanization’s Impact on Mental Health Urbanization affects mental health through overcrowding, noise pollution, and limited access to green spaces. Exploring the psychological consequences of urban living, this thesis analyzes how city environments influence mental well-being through factors such as noise, density, and lack of natural spaces.
• The Role of Literature in Empathy Cultivation Literature cultivates empathy by portraying diverse experiences, fostering emotional connections, and promoting understanding. This thesis explores how literary narratives foster empathy by encouraging readers to connect emotionally with characters from various backgrounds and circumstances.
• Effects of Online Learning on Educational Equity Online learning impacts educational equity by addressing accessibility, offering flexible options, and widening disparities. Focusing on digital education, this thesis examines how online learning platforms both address and exacerbate disparities in education access and quality.
• Media’s Influence on Public Health Attitudes Media shapes public health attitudes by disseminating health information, addressing stigmas, and promoting healthy behaviors. Examining media’s role in health communication, this thesis analyzes how media platforms influence public perceptions, spread health-related information, and contribute to behavior change.
• Impact of Technology on Family Dynamics Technology affects family dynamics by altering communication, screen time habits, and the balance between virtual and face-to-face interactions. This thesis explores how technology influences the ways families communicate, spend time together, and navigate the integration of digital devices into daily life
• Impacts of Social Media on Teen Mental Health Social media influences teen mental health through comparison, online bullying, and the pressure to curate a perfect image. Focusing on adolescent well-being, this thesis examines how social media usage affects mental health, contributing to issues such as low self-esteem, anxiety, and depression.
• The Role of Literature in Empowerment Literature empowers individuals by providing representation, voicing marginalized perspectives, and fostering a sense of agency. Addressing the transformative power of literature, this thesis explores how literary works empower individuals by offering diverse role models, amplifying underrepresented voices, and encouraging self-expression.
• Effects of Screen Time on Child Development Excessive screen time influences child development through cognitive impacts, sedentary behaviors, and altered social interactions. Investigating digital media’s impact on children, this thesis analyzes how prolonged screen time affects cognitive development, physical activity, and social skills in early childhood.
• Media’s Role in Shaping Cultural Identities Media influences cultural identities by reflecting representation, perpetuating stereotypes, and shaping societal perceptions. This thesis examines how media shapes cultural identities by influencing how different groups are represented, constructing stereotypes, and influencing cultural perceptions.
• The Impact of Online Shopping on Retail Industry Online shopping transforms the retail industry through convenience, global access, and the rise of e-commerce platforms. Focusing on the evolving retail landscape, this thesis explores how digital commerce platforms have revolutionized shopping behaviors, affecting traditional retail structures.
• The Role of Literature in Social Change Literature drives social change by sparking awareness, prompting activism, and encouraging critical engagement with societal issues. This thesis delves into how literature serves as a catalyst for social transformation by raising awareness, mobilizing readers, and advocating for change.
• Effects of Technology on Sleep Patterns Technology disrupts sleep patterns through blue light exposure, screen time before bed, and the impact on circadian rhythms. This thesis examines how technology usage, particularly before sleep, affects sleep quality, circadian rhythms, and overall well-being.
• Media’s Influence on Consumerism Media drives consumerism through advertising, influencing purchasing behavior, and shaping materialistic values. Investigating media’s impact on consumption, this thesis analyzes how advertisements, marketing strategies, and media content influence consumer choices and materialistic attitudes.
• The Impact of Virtual Reality on Education Virtual reality transforms education through immersive learning experiences, simulations, and interactive engagement. Exploring the intersection of technology and education, this thesis assesses how virtual reality enhances learning by creating immersive environments, simulations, and interactive content.
• Effects of Social Media on Friendship Dynamics Social media affects friendship dynamics by redefining connection, altering communication, and influencing group dynamics. Analyzing the digitalization of friendships, this thesis explores how social media platforms impact the nature of friendships, communication patterns, and group interactions.
• The Role of Literature in Fostering Resilience Literature fosters resilience by portraying characters’ coping strategies, resilience narratives, and encouraging emotional growth. This thesis highlights how literary narratives provide readers with insights into resilience strategies, offering examples of characters overcoming adversity and promoting emotional growth.
• Effects of Technology on Workplace Productivity Technology influences workplace productivity through automation, remote work tools, and digital communication platforms. Examining technology’s influence on work environments, this thesis assesses how digital tools enhance efficiency, promote remote collaboration, and reshape traditional work structures.
• Media’s Role in Public Opinion Formation Media shapes public opinion by framing news, influencing perceptions, and molding societal attitudes toward current events. Investigating media’s impact on public discourse, this thesis analyzes how media outlets influence public perceptions, frame news narratives, and contribute to the formation of public opinions.
• The Impact of Music on Mood Regulation Music influences mood regulation through emotional resonance, stress reduction, and the ability to evoke specific feelings. Focusing on the therapeutic effects of music, this thesis examines how music selection and listening habits impact emotional well-being, stress management, and mood enhancement.
• The Role of Literature in Environmental Awareness Literature raises environmental awareness by highlighting ecological issues, inspiring stewardship, and promoting sustainable values. Addressing the environmental impact of literature, this thesis explores how literary works contribute to environmental consciousness, advocacy for sustainable practices, and the dissemination of ecological knowledge.
• Effects of Online Communication on Language Evolution Online communication affects language evolution through text abbreviations, emojis, and the emergence of digital linguistic norms. Exploring the linguistic impact of digital communication, this thesis assesses how online platforms influence language evolution, leading to the emergence of new linguistic norms, abbreviations, and visual symbols.
• Media’s Influence on Political Participation Media shapes political participation by influencing voter engagement, political awareness, and mobilization efforts. Focusing on media’s role in democracy, this thesis analyzes how media platforms impact political engagement, disseminate information, and influence citizens’ participation in political processes.
• The Impact of Technology on Creative Expression Technology transforms creative expression through digital tools, online platforms, and innovative art forms. This thesis examines how technology empowers artists to explore new mediums, collaborate globally, and redefine creative boundaries in the digital age.
• The Role of Literature in Historical Preservation Literature preserves history by documenting cultural narratives, recording lived experiences, and offering insights into past societies. Addressing literature’s historical significance, this thesis explores how literary works serve as windows into past eras, preserving cultural memories and societal contexts.
• Effects of Video Game Violence on Aggression Video game violence influences aggression through desensitization, aggressive thoughts, and altered social behaviors. Investigating the psychological impact of gaming, this thesis analyzes how exposure to violent video games affects aggression levels, cognitive responses, and social interactions
• The Impact of Technology on Family Communication Technology alters family communication through digital devices, social media, and virtual interactions. Focusing on family dynamics, this thesis explores how technology affects communication patterns, family bonding, and the challenges of maintaining meaningful connections in the digital era.
• Effects of Social Media on Political Polarization Social media exacerbates political polarization through filter bubbles, echo chambers, and the reinforcement of ideological beliefs. Analyzing the relationship between social media and politics, this thesis investigates how online platforms contribute to the polarization of public opinion by reinforcing preexisting beliefs and narrowing exposure to diverse perspectives.
• The Role of Literature in Identity Formation Literature contributes to identity formation by reflecting cultural heritage, exploring self-discovery, and examining personal narratives. Addressing the intersection of literature and identity, this thesis explores how literary works contribute to the formation of individual and cultural identities, fostering self-awareness and cultural understanding.
• Effects of Technology on Human Relationships Technology impacts human relationships by altering social interactions, intimacy dynamics, and the balance between virtual and real-world connections. Investigating the influence of digital devices on interpersonal connections, this thesis examines how technology shapes the nature of relationships, emotional intimacy, and face-to-face interactions.
• Media’s Influence on Fear and Perception Media shapes fear and perception through sensationalism, framing, and the selective presentation of information. Focusing on media’s psychological impact, this thesis analyzes how media content affects public perceptions, triggers fear responses, and influences the framing of news events.
• The Impact of Technology on Privacy Technology challenges privacy through data collection, surveillance, and the blurring of online and offline boundaries. Addressing privacy concerns in the digital age, this thesis explores how technology threatens personal privacy by enabling data collection, surveillance practices, and the erosion of traditional boundaries between public and private spaces.
• Effects of Social Media on Body Image Social media influences body image through comparison, unrealistic beauty ideals, and promoting appearance-focused self-worth. Examining the psychological effects of digital media, this thesis assesses how social media platforms impact body image perceptions, self-esteem, and psychological well-being.
• The Role of Literature in Challenging Authority Literature challenges authority by critiquing power structures, questioning norms, and advocating for social change. Focusing on literature’s subversive potential, this thesis explores how literary works engage with themes of power, resistance, and social critique, challenging established authority and advocating for reform.
• Effects of Technology on Mental Health Technology influences mental health through screen addiction, social isolation, and the pressure to maintain an ideal online image. Investigating the relationship between technology usage and psychological well-being, this thesis analyzes how digital devices impact mental health, contributing to issues such as addiction, isolation, and negative self-comparisons.
• Media’s Role in Promoting Health Behaviors Media influences health behaviors by disseminating health information, promoting positive habits, and shaping public health narratives. Addressing media’s impact on public health, this thesis explores how media platforms contribute to health awareness, behavioral change, and the dissemination of health-related information.
• The Impact of Technology on Education Equity Technology impacts education equity by addressing access barriers, facilitating personalized learning, and promoting digital literacy. Focusing on technology’s educational implications, this thesis examines how digital tools can both bridge and exacerbate educational disparities, fostering access, inclusivity, and skills development.
• Effects of Social Media on Political Activism Social media amplifies political activism through digital mobilization, online advocacy, and the spread of social causes. Analyzing the role of technology in political engagement, this thesis assesses how social media platforms empower individuals and groups to mobilize for political change, share advocacy messages, and influence social issues.
• The Role of Literature in Promoting Empathy Literature fosters empathy by immersing readers in diverse experiences, building emotional connections, and enhancing understanding. Investigating literature’s capacity to cultivate compassion, this thesis explores how narrative empathy promotes understanding, encourages readers to embrace diverse perspectives, and fosters emotional resonance.
• Effects of Technology on Attention Span Technology impacts attention span through constant stimuli, information overload, and the allure of multitasking. Addressing technology’s cognitive effects, this thesis examines how digital devices influence attentional capabilities, cognitive focus, and the challenges of sustained concentration in a digitalized world.
• Media’s Influence on Political Disinformation Media platforms contribute to political disinformation through the spread of false information, echo chambers, and the manipulation of public opinion. Examining media’s role in disseminating misinformation, this thesis investigates how fake news, echo chambers, and algorithmic biases impact the accuracy of public discourse and democratic decision-making.
• The Impact of Technology on Creativity Technology enhances creativity through digital tools, collaborative platforms, and the democratization of creative expression. Focusing on the relationship between technology and creative processes, this thesis explores how digital innovations empower individuals to explore new artistic mediums, collaborate across boundaries, and engage in creative experimentation.
• Effects of Social Media on Political Engagement Social media influences political engagement through information dissemination, fostering online communities, and encouraging civic participation. This thesis investigates how social media platforms amplify political involvement by facilitating information-sharing, building virtual communities, and motivating individuals to engage in civic activities.
• The Role of Literature in Teaching Moral Lessons Literature imparts moral lessons by portraying ethical dilemmas, consequences of actions, and encouraging ethical reflection. Exploring literature’s moral dimensions, this thesis examines how literary narratives serve as vehicles for discussing ethical challenges, prompting readers to contemplate consequences and engage in moral reasoning.
• Effects of Technology on Physical Health Technology impacts physical health through sedentary behaviors, screen-related health issues, and disruptions to sleep patterns. Investigating the relationship between technology and physical well-being, this thesis analyzes how digital devices influence physical activity levels, posture, and overall health outcomes.
• Media’s Influence on Social Perception Media shapes social perception through portrayal, stereotypes, and influencing attitudes toward various societal groups. Analyzing media’s role in shaping public perceptions, this thesis assesses how media content constructs societal narratives, influences attitudes, and contributes to the formation of stereotypes
• The Impact of Technology on Privacy in Relationships Technology affects privacy in relationships through digital communication, surveillance concerns, and the blurring of boundaries. Focusing on the interplay of technology and personal relationships, this thesis explores how digital devices influence privacy dynamics, communication norms, and the challenges of maintaining boundaries.
• Effects of Social Media on Youth Empowerment Social media empowers youth through digital activism, amplification of voices, and the mobilization of social change. Investigating the role of social media in youth engagement, this thesis assesses how online platforms enable young individuals to advocate for causes, share perspectives, and shape societal narratives.
• The Role of Literature in Exploring Identity Literature explores identity by examining cultural heritage, personal experiences, and the journey of self-discovery. This thesis delves into how literature serves as a vehicle for individuals to explore their identities, offering insight into cultural backgrounds, personal struggles, and the quest for self-understanding.
• Effects of Technology on Memory and Cognitive Skills Technology impacts memory and cognitive skills through information overload, reliance on digital aids, and altered memory retention. Addressing technology’s cognitive effects, this thesis examines how digital devices influence memory processes, cognitive skills, and the capacity for deep learning and critical thinking.
• Media’s Influence on Political Trust Media shapes political trust through framing, information credibility, and influencing public perceptions of political figures. Analyzing media’s impact on political relationships, this thesis assesses how media coverage contributes to public trust or distrust in political institutions, leaders, and the information presented.
• The Impact of Technology on Language Evolution Technology influences language evolution through digital communication, new linguistic norms, and the emergence of online language varieties. Focusing on the linguistic impact of technology, this thesis explores how digital communication platforms contribute to the evolution of language, including the development of new forms and conventions.
• Effects of Social Media on Youth Mental Health Social media affects youth mental health through cyberbullying, the pressure to conform, and the impact of online peer comparisons. Investigating mental health challenges among young individuals, this thesis analyzes how social media contributes to anxiety, depression, and self-esteem issues among adolescents.
• The Role of Literature in Promoting Social Justice Literature advocates for social justice by depicting injustice, amplifying marginalized voices, and inspiring collective action. Addressing literature’s role in advocating for equality, this thesis explores how literary narratives illuminate social injustices, empower marginalized communities, and prompt readers to engage in activism.
• Effects of Technology on Human Productivity Technology influences human productivity through automation, digital distractions, and the challenges of multitasking. Examining the interplay of technology and productivity, this thesis assesses how digital devices both enhance and hinder efficiency, time management, and task completion.
• Media’s Influence on Cultural Appropriation Media shapes cultural appropriation through portrayal, perpetuating stereotypes, and commodifying cultural elements. Focusing on media’s impact on cultural understanding, this thesis analyzes how media content contributes to cultural appropriation by presenting distorted portrayals and commodifying cultural practices.
• The Impact of Technology on Parenting Styles Technology influences parenting styles through digital device usage, screen time management, and the challenge of balancing virtual and real-world interactions. Investigating the intersection of technology and parenting, this thesis explores how digital devices shape parenting approaches, influence family dynamics, and affect children’s development.
• Effects of Social Media on Political Information Seeking Social media influences political information seeking through personalized news feeds, echo chambers, and filter bubbles. This thesis examines how social media platforms impact the way individuals access, interpret, and seek out political information, contributing to the customization and potential polarization of news consumption.
• The Role of Literature in Addressing Mental Health Stigma Literature challenges mental health stigma by portraying mental health experiences, fostering empathy, and promoting open conversations. Focusing on the intersection of literature and mental health, this thesis explores how literary narratives contribute to destigmatizing mental health challenges by portraying characters’ struggles, emotions, and journeys to recovery.
• Effects of Technology on Social Interaction Technology influences social interaction through digital communication, altered face-to-face interactions, and the challenges of maintaining personal connections. Analyzing technology’s impact on human relationships, this thesis assesses how digital devices shape the ways individuals connect, communicate, and experience social interactions.
• Media’s Influence on Political Spin and Manipulation Media platforms contribute to political spin through biased reporting, framing, and the manipulation of public perception. Investigating media’s role in political communication, this thesis analyzes how media outlets shape public opinion by framing news narratives, promoting specific agendas, and influencing political discourse.
• The Impact of Technology on Learning Styles Technology transforms learning styles through personalized education, online resources, and the shift toward digital learning environments. Focusing on educational advancements, this thesis explores how technology accommodates diverse learning styles, fosters individualized instruction, and alters the way students engage with educational content.
• Effects of Social Media on Civic Engagement Social media influences civic engagement through digital activism, online petitions, and the mobilization of collective action. This thesis examines how social media platforms empower individuals to engage in civic activities, advocate for social change, and participate in online campaigns.
• The Role of Literature in Navigating Grief and Loss Literature provides solace in grief and loss by depicting the complexities of mourning, offering catharsis, and promoting emotional healing. Addressing literature’s role in emotional support, this thesis explores how literary narratives provide readers with ways to navigate the emotional challenges of grief, loss, and mourning.
• Effects of Technology on Environmental Awareness Technology impacts environmental awareness through online campaigns, virtual experiences, and the dissemination of environmental information. Investigating technology’s ecological impact, this thesis analyzes how digital platforms raise awareness about environmental issues, connect individuals with nature, and inspire pro-environmental behaviors.
• Media’s Influence on Public Perception of Climate Change Media shapes public perception of climate change through framing, information presentation, and the portrayal of scientific consensus. Focusing on the media’s role in environmental discourse, this thesis assesses how media coverage impacts public understanding of climate change, influencing attitudes, policy discussions, and societal responses.

3 Point Thesis Statement Examples for Argumentative Essay

• Gun Control Stricter gun control laws can reduce firearm-related violence by limiting access, implementing background checks, and regulating firearm sales. In an argumentative essay, explore the effectiveness of stricter gun control measures in curbing gun violence through access restrictions, background checks, and sales regulations.
• Climate Change Human activities are the primary drivers of climate change evidenced by rising temperatures, shrinking ice caps, and increasing carbon emissions. In this essay, argue that human actions are responsible for climate change, citing evidence like temperature increases, melting ice, and escalating carbon emissions.
• Education Reform Education reform requires revising curricula, enhancing teacher training, and implementing student-centered learning approaches to improve learning outcomes. Addressing education reform, argue that curricular updates, teacher preparation, and student-centered teaching methods are pivotal for enhancing academic achievements.
• Capital Punishment Capital punishment should be abolished due to the risk of wrongful execution, moral concerns, and lack of proven deterrence effect. In an argumentative context, advocate for the abolition of the death penalty by discussing the potential for wrongful executions, moral dilemmas, and the lack of conclusive evidence of deterrence.
• Online Privacy Stricter regulations, user education, and enhanced data encryption are necessary to safeguard online privacy in the digital age. Argue for improved online privacy by discussing the need for stringent regulations, educating users about digital risks, and implementing robust data encryption.
• Animal Testing Animal testing should be replaced with alternative methods such as in vitro testing, computer simulations, and human cell studies to ensure ethical research. Take a stance against animal testing by arguing for the adoption of humane alternatives, including in vitro experiments, computer models, and human cell research.
• School Uniforms School uniforms foster a sense of belonging, minimize socio-economic disparities, and create a focused learning environment conducive to academic success. Present a case for school uniforms, highlighting their benefits in promoting inclusivity, reducing inequality, and cultivating a focused educational environment.
• Social Media Addiction Social media addiction requires intervention through awareness campaigns, setting digital boundaries, and promoting face-to-face interactions. Argue against the harmful effects of social media addiction, advocating for strategies like awareness initiatives, self-regulation, and prioritizing offline connections.
• Genetic Engineering Genetic engineering raises ethical concerns due to potential ecological disruption, unforeseen health risks, and the alteration of natural genetic diversity. Present an argument against genetic engineering by discussing ecological impacts, health uncertainties, and potential consequences for biodiversity.
• Universal Healthcare The adoption of universal healthcare improves public health outcomes by providing equitable access to medical services, reducing financial burdens, and promoting preventive care. Advocate for universal healthcare by discussing its potential to ensure healthcare equity, alleviate financial strain, and prioritize preventative measures.

3 Point Thesis Statement Examples for an Essay

• Happiness Happiness is attainable through positive relationships, meaningful pursuits, and a balanced approach to life’s challenges. In this essay, explore the avenues to achieve happiness through fostering connections, pursuing fulfilling goals, and embracing life’s complexities.
• Travel Travel enriches personal growth by broadening cultural perspectives, encouraging adaptability, and promoting experiential learning. Discuss the benefits of travel, emphasizing its role in expanding cultural horizons, developing adaptability, and facilitating hands-on education.
• Leadership Effective leadership encompasses clear communication, empathetic understanding, and the ability to inspire and motivate others. Delve into the qualities of a successful leader, focusing on communication skills, empathy, and the capacity to inspire and lead by example.
• Dreams Pursuing dreams requires determination, overcoming obstacles, and embracing failure as a stepping stone towards eventual success. Explore the journey toward realizing dreams, emphasizing the importance of resilience, facing challenges, and learning from setbacks.
• Time Management Efficient time management involves setting priorities, utilizing effective strategies, and maintaining a healthy work-life balance. Discuss the significance of managing time wisely, covering aspects like prioritization, productivity techniques, and maintaining personal well-being.
• Healthy Eating Maintaining a healthy diet necessitates balanced nutrition, regular physical activity, and adequate sleep to promote overall well-being and academic success. In this essay, advocate for healthy eating habits by discussing the importance of nutritional balance, exercise, and sufficient sleep in supporting academic performance.
• Creativity Nurturing creativity involves embracing curiosity, seeking inspiration from various sources, and welcoming experimentation without fear of failure. Examine the facets of creativity, emphasizing curiosity-driven exploration, diverse sources of inspiration, and the courage to experiment.
• Friendship Meaningful friendships are built on trust, mutual support, and shared experiences, contributing to emotional fulfillment and personal growth. Explore the essence of friendship, discussing the core elements of trust, mutual assistance, and the impact of shared moments.
• Resilience Resilience emerges from facing adversity, developing coping strategies, and maintaining a positive outlook during challenging times. Highlight the concept of resilience, showcasing how it evolves through confronting hardships, developing coping mechanisms, and nurturing optimism.
• Nature Conservation Nature conservation demands sustainable practices, community involvement, and legislative support to preserve biodiversity and ecological balance. Discuss the importance of protecting the environment, emphasizing sustainable behaviors, community engagement, and legal measures to maintain biodiversity.

3 Point Thesis Statement Examples in Middle School

• Bullying Bullying prevention requires awareness campaigns, fostering empathy, and promoting open communication to create a safe and inclusive school environment. In middle school, discuss strategies to combat bullying by raising awareness, cultivating empathy, and encouraging open dialogue among students.
• Internet Safety Internet safety education involves responsible online behavior, recognizing digital risks, and safeguarding personal information to ensure a secure online experience. Address the importance of internet safety for middle school students, focusing on responsible online conduct, cyber awareness, and protecting personal data.
• Healthy Lifestyle Adopting a healthy lifestyle entails balanced nutrition, regular physical activity, and adequate sleep to promote overall well-being and academic success. Discuss the significance of healthy habits for middle schoolers, emphasizing the role of balanced nutrition, exercise, and sufficient sleep in supporting academic performance.
• Peer Pressure Navigating peer pressure requires assertiveness, making informed choices, and seeking positive influences to maintain personal values and self-confidence. Address the challenges of peer pressure among middle school students, advocating for strategies like assertiveness training, informed decision-making, and seeking supportive friendships.
• Environmental Awareness Fostering environmental awareness involves learning about ecosystems, practicing eco-friendly habits, and participating in conservation efforts to protect the planet. Explore the importance of environmental education for middle schoolers, encouraging them to learn about ecosystems, adopt eco-conscious behaviors, and engage in conservation projects.
• Friendship Dynamics Nurturing positive friendships involves empathy, effective communication, and resolving conflicts to foster healthy and supportive relationships. Address the complexities of middle school friendships, emphasizing empathy, communication skills, and conflict resolution techniques for building strong connections.
• Time Management Developing time management skills encompasses setting priorities, using organizational tools, and establishing routines to balance academics and leisure activities. Discuss the relevance of time management for middle school students, introducing strategies like prioritization, organization, and establishing effective routines.
• Goal Setting Goal setting involves defining aspirations, breaking tasks into manageable steps, and persevering in the face of challenges to achieve personal ambitions. Explore the concept of goal setting among middle schoolers, encouraging them to define aspirations, create actionable plans, and cultivate resilience.
• Cultural Diversity Embracing cultural diversity involves understanding different perspectives, promoting inclusion, and celebrating various traditions to create a harmonious school community. Address cultural diversity in middle school, advocating for cultural understanding, inclusivity, and the importance of respecting diverse backgrounds.
• Cyberbullying Combating cyberbullying requires reporting incidents, practicing digital citizenship, and creating a culture of kindness to ensure online safety and well-being. Discuss the implications of cyberbullying for middle schoolers, emphasizing the importance of reporting, practicing responsible online behavior, and fostering a positive digital environment.

3 Point Thesis Statement Examples in Literature

• The Great Gatsby “The Great Gatsby” portrays the disillusionment of the American Dream through characters’ pursuit of wealth, the facade of social status, and the inability to attain lasting happiness. Discuss the themes of disillusionment and the American Dream in F. Scott Fitzgerald’s novel, exploring how characters’ materialistic pursuits and social aspirations lead to unfulfilled desires.
• To Kill a Mockingbird “To Kill a Mockingbird” highlights social injustice through the lens of racism, the loss of innocence, and the importance of empathy in understanding others’ perspectives. Analyze Harper Lee’s novel, focusing on its exploration of racial inequality, the loss of innocence, and the value of empathy in addressing societal prejudices.
• Romeo and Juliet “Romeo and Juliet” examines the consequences of impulsivity, the impact of familial feuds, and the significance of love transcending societal boundaries. Explore William Shakespeare’s tragedy, discussing the themes of impulsive actions, familial conflicts, and the enduring power of love that defies societal constraints.
• 1984 “1984” critiques totalitarianism by depicting government surveillance, manipulation of language, and the suppression of individuality as dystopian manifestations of power. Analyze George Orwell’s dystopian novel, focusing on its portrayal of authoritarian control, the manipulation of information, and the degradation of personal freedoms.
• Pride and Prejudice “Pride and Prejudice” explores societal norms, gender expectations, and the complexities of love and self-discovery as characters navigate social hierarchies. Examine Jane Austen’s classic work, delving into its examination of social class, gender roles, and the transformative power of genuine affection in overcoming biases.
• The Catcher in the Rye “The Catcher in the Rye” presents the alienation of youth, the search for authenticity, and the complexities of growing up as Holden Caulfield navigates the challenges of adolescence. Discuss J.D. Salinger’s novel, focusing on the protagonist’s feelings of alienation, his quest for authenticity, and the portrayal of teenage angst and identity formation.
• The Lord of the Rings “The Lord of the Rings” explores the battle between good and evil, the hero’s journey, and the significance of fellowship as characters embark on an epic quest to save Middle-earth. Analyze J.R.R. Tolkien’s epic fantasy, discussing its themes of morality, heroism, and the power of camaraderie as characters confront the forces of darkness.
• Frankenstein “Frankenstein” delves into the consequences of unchecked ambition, the ethical implications of scientific creation, and the alienation of the outsider as Victor Frankenstein grapples with his monstrous creation. Examine Mary Shelley’s novel, addressing themes of ambition, ethics, and societal rejection as Victor Frankenstein’s scientific endeavors lead to unintended consequences.
• The Scarlet Letter “The Scarlet Letter” explores the consequences of societal judgment, the complexities of sin and redemption, and the resilience of the human spirit as Hester Prynne navigates the aftermath of her actions. Analyze Nathaniel Hawthorne’s work, discussing its examination of guilt, societal norms, and the capacity for personal growth in the face of adversity.
• Brave New World “Brave New World” critiques a dystopian future by depicting a society driven by consumerism, the suppression of individuality, and the manipulation of happiness as the ultimate goal. Explore Aldous Huxley’s dystopian vision, discussing its commentary on technological control, the pursuit of pleasure, and the loss of authentic human experience.

3 Point Thesis Statement Examples for Graphic Organizers

• Solar System Understanding the solar system involves recognizing the sun as the center, identifying planets and their characteristics, and comprehending the roles of asteroids, comets, and moons. Discuss the solar system using a graphic organizer, highlighting its key components including the sun, planets, asteroids, comets, and moons, along with their distinctive features.
• Ecosystems Exploring ecosystems involves categorizing biomes, understanding food chains and webs, and recognizing the importance of biodiversity in maintaining ecological balance. Utilize a graphic organizer to depict various biomes within ecosystems, illustrate food chains and webs, and emphasize the significance of biodiversity for ecological stability.
• Literary Elements Analyzing literature entails identifying plot elements, character traits, and thematic concepts to gain a comprehensive understanding of narrative structure and meaning. Create a graphic organizer to analyze literary works, mapping out key elements such as plot, characters, and themes to enhance comprehension of narrative elements.
• Historical Events Studying historical events requires sequencing chronological occurrences, contextualizing historical contexts, and identifying influential figures and their contributions. Construct a graphic organizer to explore historical events, arranging them chronologically, providing contextual information, and highlighting notable individuals and their impacts.
• Plant Life Cycle Exploring the plant life cycle involves identifying stages from seed germination to reproduction, understanding the roles of roots, stems, leaves, and flowers, and grasping the significance of pollination. Employ a graphic organizer to depict the plant life cycle, depicting stages from seed germination to pollination and reproduction, while illustrating the roles of different plant parts.
• Literary Genres Understanding literary genres requires categorizing fiction, non-fiction, poetry, drama, and identifying distinguishing characteristics that define each genre’s narrative style. Use a graphic organizer to differentiate literary genres, classifying fiction, non-fiction, poetry, and drama while highlighting the unique features that define each genre.
• Elements of a Story Analyzing the elements of a story involves identifying the exposition, rising action, climax, falling action, and resolution to gain insight into narrative structure and development. Create a graphic organizer to explore the elements of a story, mapping out the key stages from exposition to resolution, enhancing comprehension of narrative progression.
• Food Groups Understanding dietary balance entails categorizing food groups such as fruits, vegetables, grains, proteins, and dairy, and recognizing their nutritional contributions to overall health. Utilize a graphic organizer to depict food groups, categorizing fruits, vegetables, grains, proteins, and dairy while emphasizing their roles in providing essential nutrients.
• Biographical Information Exploring biographies involves organizing key details like birth, achievements, contributions, and impact to gain insights into notable individuals’ lives and legacies. Construct a graphic organizer to analyze biographical information, arranging details such as birth, accomplishments, significant contributions, and lasting impact on society.
• Cause and Effect Relationships Understanding cause and effect relationships entails identifying triggers and outcomes, recognizing the interconnectedness of events, and comprehending the implications of actions. Design a graphic organizer to explore cause and effect relationships, mapping out causal factors and corresponding effects to illustrate the interconnected nature of events.

Free 3 Point Thesis Statement Worksheets Download

Download our free 3 Point Thesis Statement Worksheets to enhance your writing skills. These comprehensive resources provide structured guidance on crafting impactful thesis statements for various topics. Through step-by-step exercises, you’ll learn to formulate clear arguments with three supporting points, fostering effective communication and analytical thinking. Elevate your essay writing by mastering the art of concise and persuasive thesis statements with our downloadable worksheets.

3 Point Thesis Statement Worksheet

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How to Write a 3 Point Thesis Statement? – Step by Step Guide

Crafting a compelling 3 Point Thesis Statement involves careful planning and a structured approach. Follow this step-by-step guide to create a clear and impactful thesis that effectively outlines your main argument and supporting points:

• Choose Your Topic: Select a specific topic that you want to address in your essay. Ensure it’s focused enough to be thoroughly explored within the scope of your work.
• Identify Your Main Argument: Determine the central point or argument you want to make about the chosen topic. This main idea will serve as the foundation for your thesis statement.
• Brainstorm Supporting Points: Identify three key points that support and reinforce your main argument. These points will guide your essay’s structure and content.
• Craft Your Thesis Statement: Combine your main argument and the three supporting points into a single, concise sentence. Ensure it clearly conveys the overall message of your essay.
• Order and Coherence: Arrange your supporting points logically. Typically, present them in the order you’ll address them in your essay, from strongest to weakest or chronologically.
• Avoid Ambiguity: Make sure your thesis statement is specific and unambiguous. Avoid vague language that might confuse or mislead readers.
• Precision and Clarity: Use clear and precise language in your thesis statement. Each word should contribute to the overall clarity and accuracy of your message.
• Revise for Consistency: Check that your thesis statement aligns with the content of your essay. Any deviations should be addressed to maintain coherence.
• Seek Feedback: Share your thesis statement with peers or mentors for feedback. Their insights can help you refine and strengthen your argument.
• Refine and Edit: Revise your thesis statement based on the feedback you receive. Edit for grammar, style, and conciseness.
• Finalize Your Thesis Statement: Once satisfied, incorporate your refined thesis statement into your essay’s introduction, ensuring it provides a roadmap for readers.

By following this step-by-step guide, you can create a powerful 3 Point Thesis Statement that effectively communicates your main argument and supporting points, setting the tone for a well-structured and persuasive essay.

Tips for Writing a 3 Point Thesis Statment

• Clarity is Key: Keep your thesis statement clear and straightforward, avoiding vague or convoluted language.
• Singular Focus: Center your thesis around a single, focused argument to maintain a clear message.
• Strong Supporting Points: Select three robust supporting points that directly bolster your main argument.
• Parallel Structure: Use consistent grammatical structure for your supporting points to enhance organization.
• Logical Order: Arrange supporting points logically, from strongest to weakest or in a coherent sequence.
• Specific Examples: Back up your points with concrete evidence, avoiding general statements.
• Avoid First-Person: Keep your thesis objective by refraining from using first-person pronouns.
• Highlight Importance: Explain the significance or broader implications of your main argument and points.
• Feedback Matters: Seek input from others to refine and strengthen your thesis statement.
• Connect and Transition: Ensure your thesis smoothly leads into the content of your essay’s body.

Mastering the art of crafting impactful 3 Point Thesis Statements elevates your writing prowess. With a clear main argument and well-chosen supporting points, your essays gain depth and structure. Following expert tips ensures clarity, conciseness, and logical organization. This skill empowers you to communicate effectively, fostering a deeper connection with readers and enhancing the overall impact of your work.

Text prompt

• Instructive
• Professional

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