types of phd research methods

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15 kinds of research methodologies for phd. pupils, basic research.

Pure research or fundamental research or basic research zooms on enhancing scientific knowledge for the exhaustive understanding of a topic or certain natural phenomena, essentially in natural sciences; knowledge that is obtained for the purpose of knowledge it is called fundamental research.

1.Applied research

Research that covers real life applications of the natural sciences; aimed at offering an answer to particular practical issues and develops novel technologies

2.Fixed research versus flexible research

In fixed research, the design of the study is fixed prior to the main phase of data gathering; moreover, fixed designs are essentially theoretical. Variables that need to be controlled and measured need to be known in advance and they are measured quantitatively.

3.Quantitative research and qualitative research

Quantitative research denotes gauging phenomena in various grades; on the other hand, qualitative research sometimes deems Boolean measurements alone; solution can be studied qualitatively for its appropriateness. However, comparison between candidate solutions requires quantitative observation.

4.Experimental research and non-experimental research

In an experimental design , operationalize the variables to be measured; moreover, operationalize in the best manner. Consider the study expectations, outcome measurement, variable measurement, and the methods to answer research questions.

Think of the practical limitations such as the availability of data-sets and experimental set-ups that represent actual scenarios.

5.Exploratory research and confirmatory research

Confirmatory research tests a priori hypotheses—outcome predictions done prior to the measurement stage. Such a priori hypotheses are usually derived from a theory or the results of previous studies.

Exploratory research generates a posteriori hypotheses by investigating a data-set and ascertaining potential connection between variables.

6.Explanatory research or casual research

Causal research is also called explanatory research ; conducted to ascertain the extent and type of cause-effect relationships. Causal research are conducted to evaluate effects of specific changes on existing norms, various processes etc.

7.Descriptive research

Descriptive research is the available statement of affairs; researcher has no control over variable. Descriptive studies are characterised as simply an effort to ascertain, define or recognize.  Not “why it is that way” nor “how it came to be,” which is the objective of analytical research.

8.Historical research

Historical research explores and explains the meanings, phases and traits of a phenomena or process at a certain phase of time in the past; historical research is a research strategy from the research of history.

9.Casual comparative research

Also called as “ex-post facto” research (In Latin, implies “after the fact”); researchers determine the causes or consequences of differences that already exist between or among groups of individuals.

An effort to ascertain a causative relationship between an independent variable and a dependent variable; relationship between the independent variable and dependent variable are usually a suggested relationship (not proved yet) because you do not have complete control over the independent variable

10.Correlational research

Correlational research is a form of non-experimental research technique wherein a researcher measures 2 variables and assesses the statistical connection between them with no influence from any external variable.

The correlation between two variables is given through correlation coefficient, which is a statistical measure that calculates the strength of the relationship between two variables that is a value measured between -1 and +1.

11.Evaluation research method

Evaluation research technique is known as program evaluation and refers to a research purpose instead of a particular technique; objective is to assess the effect of social involvements such as new treatment techniques, innovations in services, etc.

A form of applied research to have some real-world effect. Methods such as surveys and experiments are used in evaluation research.

12.Formative and summative evaluation

While learning is in progress, formative assessment offers feedback and information; measures participant’s progress and also assess researcher’s own progress as well.

For example, when implementing a new program, you can determine whether or not the activity should be used again (or modified) with the help of observation and/or surveying.

Summative assessment happens after the learning has ended and offers info and feedback to sum up the process; essentially, no formal learning is happening at this phase other than incidental learning which might take place through the completion of program.

13.Diagnostic research

Descriptive research studies define the characteristics of a particular individual, or of a group.

Studies showing whether certain variables are linked are examples of diagnostic research.

Researcher defines what he or she wants to measure and finds adequate methods for measuring it along with a clear description of ‘population’.

Aim is to obtain complete and accurate information. And the researcher plans the procedure carefully.

14.Prognostic research

Prognostic research (specifically in clinical research) examines chosen predictive variables and risk factors; prognostic research assesses influence on the outcome of a disease. Clinicians have a better understanding of the history of the ailment.

This understanding facilitates clinical decision-making via providing apt treatment alternatives and helps to predict accurate disease outcomes.

Assessing prognostic studies involves ascertaining the internal validity of the study design and assessing the effects of bias or systemic errors.

15.Action research

A systematic inquiry for improving and/or honing researchers’ actions. Researchers find it an empowering experience.

Action research has positive result for various reasons; most important is that action research is pertinent to the research participants.

Relevance is assured because the aim of each research project is ascertained by the researchers, who are also the main beneficiaries of the research observations.

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15 Types of Research Methods

Chris Drew (PhD)

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]

Learn about our Editorial Process

Research methods refer to the strategies, tools, and techniques used to gather and analyze data in a structured way in order to answer a research question or investigate a hypothesis (Hammond & Wellington, 2020).

Generally, we place research methods into two categories: quantitative and qualitative. Each has its own strengths and weaknesses, which we can summarize as:

• Quantitative research can achieve generalizability through scrupulous statistical analysis applied to large sample sizes.
• Qualitative research achieves deep, detailed, and nuance accounts of specific case studies, which are not generalizable.

Some researchers, with the aim of making the most of both quantitative and qualitative research, employ mixed methods, whereby they will apply both types of research methods in the one study, such as by conducting a statistical survey alongside in-depth interviews to add context to the quantitative findings.

Below, I’ll outline 15 common research methods, and include pros, cons, and examples of each .

Types of Research Methods

Research methods can be broadly categorized into two types: quantitative and qualitative.

• Quantitative methods involve systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques, providing an in-depth understanding of a specific concept or phenomenon (Schweigert, 2021). The strengths of this approach include its ability to produce reliable results that can be generalized to a larger population, although it can lack depth and detail.
• Qualitative methods encompass techniques that are designed to provide a deep understanding of a complex issue, often in a specific context, through collection of non-numerical data (Tracy, 2019). This approach often provides rich, detailed insights but can be time-consuming and its findings may not be generalizable.

These can be further broken down into a range of specific research methods and designs:

Combining the two methods above, mixed methods research mixes elements of both qualitative and quantitative research methods, providing a comprehensive understanding of the research problem . We can further break these down into:

• Sequential Explanatory Design (QUAN→QUAL): This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.
• Sequential Exploratory Design (QUAL→QUAN): This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

Let’s explore some methods and designs from both quantitative and qualitative traditions, starting with qualitative research methods.

Qualitative Research Methods

Qualitative research methods allow for the exploration of phenomena in their natural settings, providing detailed, descriptive responses and insights into individuals’ experiences and perceptions (Howitt, 2019).

These methods are useful when a detailed understanding of a phenomenon is sought.

1. Ethnographic Research

Ethnographic research emerged out of anthropological research, where anthropologists would enter into a setting for a sustained period of time, getting to know a cultural group and taking detailed observations.

Ethnographers would sometimes even act as participants in the group or culture, which many scholars argue is a weakness because it is a step away from achieving objectivity (Stokes & Wall, 2017).

In fact, at its most extreme version, ethnographers even conduct research on themselves, in a fascinating methodology call autoethnography .

The purpose is to understand the culture, social structure, and the behaviors of the group under study. It is often useful when researchers seek to understand shared cultural meanings and practices in their natural settings.

However, it can be time-consuming and may reflect researcher biases due to the immersion approach.

Example of Ethnography

Liquidated: An Ethnography of Wall Street  by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

2. Phenomenological Research

Phenomenological research is a qualitative method focused on the study of individual experiences from the participant’s perspective (Tracy, 2019).

It focuses specifically on people’s experiences in relation to a specific social phenomenon ( see here for examples of social phenomena ).

This method is valuable when the goal is to understand how individuals perceive, experience, and make meaning of particular phenomena. However, because it is subjective and dependent on participants’ self-reports, findings may not be generalizable, and are highly reliant on self-reported ‘thoughts and feelings’.

Example of Phenomenological Research

A phenomenological approach to experiences with technology  by Sebnem Cilesiz represents a good starting-point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

3. Historical Research

Historical research is a qualitative method involving the examination of past events to draw conclusions about the present or make predictions about the future (Stokes & Wall, 2017).

As you might expect, it’s common in the research branches of history departments in universities.

This approach is useful in studies that seek to understand the past to interpret present events or trends. However, it relies heavily on the availability and reliability of source materials, which may be limited.

Common data sources include cultural artifacts from both material and non-material culture , which are then examined, compared, contrasted, and contextualized to test hypotheses and generate theories.

Example of Historical Research

A historical research example might be a study examining the evolution of gender roles over the last century. This research might involve the analysis of historical newspapers, advertisements, letters, and company documents, as well as sociocultural contexts.

4. Content Analysis

Content analysis is a research method that involves systematic and objective coding and interpreting of text or media to identify patterns, themes, ideologies, or biases (Schweigert, 2021).

A content analysis is useful in analyzing communication patterns, helping to reveal how texts such as newspapers, movies, films, political speeches, and other types of ‘content’ contain narratives and biases.

However, interpretations can be very subjective, which often requires scholars to engage in practices such as cross-comparing their coding with peers or external researchers.

Content analysis can be further broken down in to other specific methodologies such as semiotic analysis, multimodal analysis , and discourse analysis .

Example of Content Analysis

How is Islam Portrayed in Western Media?  by Poorebrahim and Zarei (2013) employs a type of content analysis called critical discourse analysis (common in poststructuralist and critical theory research ). This study by Poorebrahum and Zarei combs through a corpus of western media texts to explore the language forms that are used in relation to Islam and Muslims, finding that they are overly stereotyped, which may represent anti-Islam bias or failure to understand the Islamic world.

5. Grounded Theory Research

Grounded theory involves developing a theory  during and after  data collection rather than beforehand.

This is in contrast to most academic research studies, which start with a hypothesis or theory and then testing of it through a study, where we might have a null hypothesis (disproving the theory) and an alternative hypothesis (supporting the theory).

Grounded Theory is useful because it keeps an open mind to what the data might reveal out of the research. It can be time-consuming and requires rigorous data analysis (Tracy, 2019).

Grounded Theory Example

Developing a Leadership Identity   by Komives et al (2005) employs a grounded theory approach to develop a thesis based on the data rather than testing a hypothesis. The researchers studied the leadership identity of 13 college students taking on leadership roles. Based on their interviews, the researchers theorized that the students’ leadership identities shifted from a hierarchical view of leadership to one that embraced leadership as a collaborative concept.

6. Action Research

Action research is an approach which aims to solve real-world problems and bring about change within a setting. The study is designed to solve a specific problem – or in other words, to take action (Patten, 2017).

This approach can involve mixed methods, but is generally qualitative because it usually involves the study of a specific case study wherein the researcher works, e.g. a teacher studying their own classroom practice to seek ways they can improve.

Action research is very common in fields like education and nursing where practitioners identify areas for improvement then implement a study in order to find paths forward.

Action Research Example

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing   by Ellison and Drew was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

7. Natural Observational Research

Observational research can also be quantitative (see: experimental research), but in naturalistic settings for the social sciences, researchers tend to employ qualitative data collection methods like interviews and field notes to observe people in their day-to-day environments.

This approach involves the observation and detailed recording of behaviors in their natural settings (Howitt, 2019). It can provide rich, in-depth information, but the researcher’s presence might influence behavior.

While observational research has some overlaps with ethnography (especially in regard to data collection techniques), it tends not to be as sustained as ethnography, e.g. a researcher might do 5 observations, every second Monday, as opposed to being embedded in an environment.

Observational Research Example

A researcher might use qualitative observational research to study the behaviors and interactions of children at a playground. The researcher would document the behaviors observed, such as the types of games played, levels of cooperation , and instances of conflict.

8. Case Study Research

Case study research is a qualitative method that involves a deep and thorough investigation of a single individual, group, or event in order to explore facets of that phenomenon that cannot be captured using other methods (Stokes & Wall, 2017).

Case study research is especially valuable in providing contextualized insights into specific issues, facilitating the application of abstract theories to real-world situations (Patten, 2017).

However, findings from a case study may not be generalizable due to the specific context and the limited number of cases studied (Walliman, 2021).

See More: Case Study Advantages and Disadvantages

Example of a Case Study

Scholars conduct a detailed exploration of the implementation of a new teaching method within a classroom setting. The study focuses on how the teacher and students adapt to the new method, the challenges encountered, and the outcomes on student performance and engagement. While the study provides specific and detailed insights of the teaching method in that classroom, it cannot be generalized to other classrooms, as statistical significance has not been established through this qualitative approach.

Quantitative Research Methods

Quantitative research methods involve the systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques (Pajo, 2022). The focus is on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

9. Experimental Research

Experimental research is a quantitative method where researchers manipulate one variable to determine its effect on another (Walliman, 2021).

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

This type of research is useful in situations where researchers want to determine causal relationships between variables. However, experimental conditions may not reflect real-world conditions.

Example of Experimental Research

A researcher may conduct an experiment to determine the effects of a new educational approach on student learning outcomes. Students would be randomly assigned to either the control group (traditional teaching method) or the experimental group (new educational approach).

10. Surveys and Questionnaires

Surveys and questionnaires are quantitative methods that involve asking research participants structured and predefined questions to collect data about their attitudes, beliefs, behaviors, or characteristics (Patten, 2017).

Surveys are beneficial for collecting data from large samples, but they depend heavily on the honesty and accuracy of respondents.

They tend to be seen as more authoritative than their qualitative counterparts, semi-structured interviews, because the data is quantifiable (e.g. a questionnaire where information is presented on a scale from 1 to 10 can allow researchers to determine and compare statistical means, averages, and variations across sub-populations in the study).

Example of a Survey Study

A company might use a survey to gather data about employee job satisfaction across its offices worldwide. Employees would be asked to rate various aspects of their job satisfaction on a Likert scale. While this method provides a broad overview, it may lack the depth of understanding possible with other methods (Stokes & Wall, 2017).

11. Longitudinal Studies

Longitudinal studies involve repeated observations of the same variables over extended periods (Howitt, 2019). These studies are valuable for tracking development and change but can be costly and time-consuming.

With multiple data points collected over extended periods, it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes a detailed analysis of change possible.

Perhaps the most relatable example of a longitudinal study is a national census, which is taken on the same day every few years, to gather comparative demographic data that can show how a nation is changing over time.

While longitudinal studies are commonly quantitative, there are also instances of qualitative ones as well, such as the famous 7 Up study from the UK, which studies 14 individuals every 7 years to explore their development over their lives.

Example of a Longitudinal Study

A national census, taken every few years, uses surveys to develop longitudinal data, which is then compared and analyzed to present accurate trends over time. Trends a census can reveal include changes in religiosity, values and attitudes on social issues, and much more.

12. Cross-Sectional Studies

Cross-sectional studies are a quantitative research method that involves analyzing data from a population at a specific point in time (Patten, 2017). They provide a snapshot of a situation but cannot determine causality.

This design is used to measure and compare the prevalence of certain characteristics or outcomes in different groups within the sampled population.

The major advantage of cross-sectional design is its ability to measure a wide range of variables simultaneously without needing to follow up with participants over time.

However, cross-sectional studies do have limitations . This design can only show if there are associations or correlations between different variables, but cannot prove cause and effect relationships, temporal sequence, changes, and trends over time.

Example of a Cross-Sectional Study

Our longitudinal study example of a national census also happens to contain cross-sectional design. One census is cross-sectional, displaying only data from one point in time. But when a census is taken once every few years, it becomes longitudinal, and so long as the data collection technique remains unchanged, identification of changes will be achievable, adding another time dimension on top of a basic cross-sectional study.

13. Correlational Research

Correlational research is a quantitative method that seeks to determine if and to what degree a relationship exists between two or more quantifiable variables (Schweigert, 2021).

This approach provides a fast and easy way to make initial hypotheses based on either positive or  negative correlation trends  that can be observed within dataset.

While correlational research can reveal relationships between variables, it cannot establish causality.

Methods used for data analysis may include statistical correlations such as Pearson’s or Spearman’s.

Example of Correlational Research

A team of researchers is interested in studying the relationship between the amount of time students spend studying and their academic performance. They gather data from a high school, measuring the number of hours each student studies per week and their grade point averages (GPAs) at the end of the semester. Upon analyzing the data, they find a positive correlation, suggesting that students who spend more time studying tend to have higher GPAs.

14. Quasi-Experimental Design Research

Quasi-experimental design research is a quantitative research method that is similar to experimental design but lacks the element of random assignment to treatment or control.

Instead, quasi-experimental designs typically rely on certain other methods to control for extraneous variables.

The term ‘quasi-experimental’ implies that the experiment resembles a true experiment, but it is not exactly the same because it doesn’t meet all the criteria for a ‘true’ experiment, specifically in terms of control and random assignment.

Quasi-experimental design is useful when researchers want to study a causal hypothesis or relationship, but practical or ethical considerations prevent them from manipulating variables and randomly assigning participants to conditions.

Example of Quasi-Experimental Design

A researcher wants to study the impact of a new math tutoring program on student performance. However, ethical and practical constraints prevent random assignment to the “tutoring” and “no tutoring” groups. Instead, the researcher compares students who chose to receive tutoring (experimental group) to similar students who did not choose to receive tutoring (control group), controlling for other variables like grade level and previous math performance.

Related: Examples and Types of Random Assignment in Research

15. Meta-Analysis Research

Meta-analysis statistically combines the results of multiple studies on a specific topic to yield a more precise estimate of the effect size. It’s the gold standard of secondary research .

Meta-analysis is particularly useful when there are numerous studies on a topic, and there is a need to integrate the findings to draw more reliable conclusions.

Some meta-analyses can identify flaws or gaps in a corpus of research, when can be highly influential in academic research, despite lack of primary data collection.

However, they tend only to be feasible when there is a sizable corpus of high-quality and reliable studies into a phenomenon.

Example of a Meta-Analysis

The power of feedback revisited (Wisniewski, Zierer & Hattie, 2020) is a meta-analysis that examines 435 empirical studies research on the effects of feedback on student learning. They use a random-effects model to ascertain whether there is a clear effect size across the literature. The authors find that feedback tends to impact cognitive and motor skill outcomes but has less of an effect on motivational and behavioral outcomes.

Choosing a research method requires a lot of consideration regarding what you want to achieve, your research paradigm, and the methodology that is most valuable for what you are studying. There are multiple types of research methods, many of which I haven’t been able to present here. Generally, it’s recommended that you work with an experienced researcher or research supervisor to identify a suitable research method for your study at hand.

Hammond, M., & Wellington, J. (2020). Research methods: The key concepts . New York: Routledge.

Howitt, D. (2019). Introduction to qualitative research methods in psychology . London: Pearson UK.

Pajo, B. (2022). Introduction to research methods: A hands-on approach . New York: Sage Publications.

Patten, M. L. (2017). Understanding research methods: An overview of the essentials . New York: Sage

Schweigert, W. A. (2021). Research methods in psychology: A handbook . Los Angeles: Waveland Press.

Stokes, P., & Wall, T. (2017). Research methods . New York: Bloomsbury Publishing.

Tracy, S. J. (2019). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact . London: John Wiley & Sons.

Walliman, N. (2021). Research methods: The basics. London: Routledge.

• 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
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 50 Incentives to Give to Students

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How To Choose Your Research Methodology

Qualitative vs quantitative vs mixed methods.

By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021

Without a doubt, one of the most common questions we receive at Grad Coach is “ How do I choose the right methodology for my research? ”. It’s easy to see why – with so many options on the research design table, it’s easy to get intimidated, especially with all the complex lingo!

In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.

Overview: Choosing Your Methodology

Understanding the options – Qualitative research – Quantitative research – Mixed methods-based research

Choosing a research methodology – Nature of the research – Research area norms – Practicalities

1. Understanding the options

Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative , quantitative and mixed methods -based research. Each of these options takes a different methodological approach.

Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words , descriptions , concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.

Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture . In contrast to this, quantitative methods are usually used to confirm or test hypotheses . In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.

• Uses an inductive approach
• Is used to build theories
• Takes a subjective approach
• Adopts an open and flexible approach
• The researcher is close to the respondents
• Interviews and focus groups are oftentimes used to collect word-based data.
• Generally, draws on small sample sizes
• Uses qualitative data analysis techniques (e.g. content analysis , thematic analysis , etc)
• Uses a deductive approach
• Is used to test theories
• Takes an objective approach
• Adopts a closed, highly planned approach
• The research is disconnected from respondents
• Surveys or laboratory equipment are often used to collect number-based data.
• Generally, requires large sample sizes
• Uses statistical analysis techniques to make sense of the data

Mixed methods -based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.

In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach , unless the nature of their study truly warrants a mixed-methods approach.

The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job. 

Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.

2. How to choose a research methodology

To choose the right research methodology for your dissertation or thesis, you need to consider three important factors . Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling , data collection methods and analysis techniques (we discuss these separately in other posts ).

The three factors you need to consider are:

• The nature of your research aims, objectives and research questions
• The methodological approaches taken in the existing literature
• Practicalities and constraints

Let’s take a look at each of these.

Factor #1: The nature of your research

As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions .

But, what types of research exist?

Broadly speaking, research can fall into one of three categories:

• Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
• Confirmatory – confirming a potential theory or hypothesis by testing it empirically
• A mix of both – building a potential theory or hypothesis and then testing it

As a rule of thumb, exploratory research tends to adopt a qualitative approach , whereas confirmatory research tends to use quantitative methods . This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.

Let’s look at an example in action.

If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.

If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs .

So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims , objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.

The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.

If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.

Need a helping hand?

Factor #2: The disciplinary norms

Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.

A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments .

Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.

Factor #3: Practicalities

When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design ) and doing what’s practical , given your constraints . This is the nature of doing research and there are always trade-offs, as with anything else.

But what constraints, you ask?

When you’re evaluating your methodological options, you need to consider the following constraints:

• Data access
• Equipment and software
• Your knowledge and skills

Let’s look at each of these.

Constraint #1: Data access

The first practical constraint you need to consider is your access to data . If you’re going to be undertaking primary research , you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews , you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.

If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.

So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.

Constraint #2: Time

The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements . Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.

Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional . For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon. 

Constraint #3: Money

As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget .

Some of the costs that may arise include:

• Software costs – e.g. survey hosting services, analysis software, etc.
• Promotion costs – e.g. advertising a survey to attract respondents
• Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
• Equipment rental costs – e.g. recording equipment, lab equipment, etc.
• Travel costs
• Food & beverages

These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.

Constraint #4: Equipment & software

Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.

Constraint #5: Your knowledge and skillset

The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.

Some of the questions you should ask yourself are:

• Am I more of a “numbers person” or a “words person”?
• How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
• How much do I know about the software and/or hardware that I’ll potentially use?
• How excited am I to learn new research skills and gain new knowledge?
• How much time do I have to learn the things I need to learn?

Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.

So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.

Recap: Choosing a methodology

In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:

• Exploratory
• Confirmatory
• Combination
• Research area norms
• Hardware and software
• Your knowledge and skillset

If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service , or book a free consultation with a friendly Grad Coach.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

Very useful and informative especially for beginners

Nice article! I’m a beginner in the field of cybersecurity research. I am a Telecom and Network Engineer and Also aiming for PhD scholarship.

I find the article very informative especially for my decitation it has been helpful and an eye opener.

Hi I am Anna ,

I am a PHD candidate in the area of cyber security, maybe we can link up

The Examples shows by you, for sure they are really direct me and others to knows and practices the Research Design and prepration.

I found the post very informative and practical.

I struggle so much with designs of the research for sure!

I’m the process of constructing my research design and I want to know if the data analysis I plan to present in my thesis defense proposal possibly change especially after I gathered the data already.

Thank you so much this site is such a life saver. How I wish 1-1 coaching is available in our country but sadly it’s not.

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What are acceptable dissertation research methods?

August 16, 2023

Reading time:  3–4 minutes

Doctoral research is the cornerstone of a PhD program .

In order to write a dissertation, you must complete extensive, detailed research. Depending on your area of study, different types of research methods will be appropriate to complete your work.

“The choice of research method depends on the questions you hope to answer with your research,” says Curtis Brant, PhD, Capella University dean of research and scholarship.

Once you’ve identified your research problem, you’ll employ the methodology best suited for solving the problem.

There are two primary dissertation research methods: qualitative and quantitative.

Qualitative

Qualitative research focuses on examining the topic via cultural phenomena, human behavior or belief systems. This type of research uses interviews, open-ended questions or focus groups to gain insight into people’s thoughts and beliefs around certain behaviors and systems.

Dr. Brant says there are several approaches to qualitative inquiry. The three most routinely used include:

Generic qualitative inquiry. The researcher focuses on people’s experiences or perceptions in the real world. This often includes, but is not limited to, subjective opinions, attitudes and beliefs .

Case study. The researcher performs an in-depth exploration of a program, event, activity or process with an emphasis on the experience of one or more individuals. The focus of this kind of inquiry must be defined and often includes more than one set of data, such as interviews and field notes, observations or other qualitative data.

Phenomenological. The researcher identifies lived experiences associated with how an individual encounters and engages with the real world .

Qualitative research questions seek to discover:

• A participant’s verbal descriptions of a phenomenon being investigated
•  A researcher’s observations of the phenomenon being investigated
• An integrated interpretation of participant’s descriptions and researchers observations

Quantitative

Quantitative research involves the empirical investigation of observable and measurable variables. It is used for theory testing, predicting outcomes or determining relationships between and among variables using statistical analysis.

According to Dr. Brant, there are two primary data sources for quantitative research.

Surveys: Surveys involve asking people a set of questions, usually testing for linear relationships, statistical differences or statistical independence. This approach is common in correlation research designs.

Archival research (secondary data analysis). Archival research involves using preexisting data to answer research questions instead of collecting data from active human participants.

Quantitative research questions seek to address:

• Descriptions of variables being investigated
• Measurements of relationships between (at least two) variables
• Differences between two or more groups’ scores on a variable or variables

Which method should you choose?

Choosing a qualitative or quantitative methodology for your research will be based on the nature of the questions you ask, the preferred method in your field, the feasibility of the approach and other factors. Many programs offer doctoral mentors and support teams that can help guide you throughout the process.

Capella University offers PhD and professional doctorate degree programs ranging from business to education and health to technology. Learn more about Capella doctoral programs and doctoral support.

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Topic selection & proposal development, enquire now, software implementation using matlab, questionnaire designing & data analysis, chapters writing & journal papers, 5 different types of research methodology for 2024.

Research Methodology refers to the systematic process used to conduct and analyze research. It involves a set of procedures and techniques employed to gather, organize, and interpret data. Various types of research methodology , such as qualitative and quantitative methods, form the foundation for investigating and understanding diverse phenomena. 

Diverse research methodology provide a spectrum of advantages in scientific exploration. Qualitative methodologies, such as interviews and observations, delve deep into understanding human behavior and motivations. Quantitative approaches, like surveys and experiments, offer precise numerical data for statistical analysis. Mixed-methods enable a comprehensive view by merging qualitative and quantitative strengths. Experimental methods establish cause-and-effect relationships, while case studies offer in-depth insights into specific instances. Each methodology caters to different research needs, fostering a nuanced understanding of complex phenomena and contributing to the richness and depth of scholarly inquiry.

This blog is your guide to the Top 5 types of research methods that haven’t been fully tapped into yet. We’re talking about different ways to do research, the kind that hasn’t been widely used or discovered. It’s crucial to stay on top of these categories of research methodology because as the world moves forward, so does the way we study and understand things. So, we’ll be checking out the latest and coolest Research methodology types , from new technologies to fresh ways of combining different fields of study. 

Different types of methodology in research

Research methodology encompasses a variety of approaches and techniques to gather and analyze data. Here are some Different types of methodology in research:

Qualitative Methodology:

In-depth exploration of attitudes, behaviors, and motivations.

Utilizes methods like interviews, focus groups, and content analysis.

Quantitative Methodology:

Focuses on numerical data and statistical analysis.

Involves surveys, experiments, and structured observations.

Mixed-Methods Approach:

Integrates both qualitative and quantitative methods.

Offers a thorough comprehension of the research problem.

Experimental Research:

Investigates cause-and-effect relationships.

Involves controlled experiments with manipulated variables.

Survey Research:

Gathers data from a selected group through structured questionnaires.

Examines trends, attitudes, and opinions.

Case Study Methodology:

In-depth analysis of a specific instance or case.

Offers detailed insights into complex phenomena.

Action Research:

Involves collaboration between researchers and practitioners.

Aims to solve real-world problems through iterative cycles of planning, acting, observing, and reflecting.

Ethnographic Research:

Immersive study of a specific group or culture.

Requires prolonged engagement and participant observation.

Methodology 1: Neurobiological Methodology

Neurobiological Methodology stands at the forefront of methodology in research paper, bridging the realms of neuroscience and traditional research methodologies. This is one of the Research methodology types which aims to unravel the intricacies of human cognition and behavior by integrating cutting-edge brain imaging techniques with established research methods.

Key Components:

Neuroimaging Technologies: Utilizes advanced technologies such as fMRI (functional Magnetic Resonance Imaging) and EEG (Electroencephalography) for all the research methodologies including exploratory research in research methodology. Enables real-time monitoring of brain activity, offering insights into cognitive processes during various tasks.

Biometric Data Integration: Incorporates biometric data, including heart rate variability and skin conductance, to supplement neurobiological findings. Provides a comprehensive understanding of emotional responses and physiological changes related to cognitive activities.

Experimental Designs with Neural Correlates: Designs experiments that correlate specific neural activities with behavioral responses. Allows researchers to identify neural markers associated with decision-making, memory, and learning.

Cross-Disciplinary Collaboration: Encourages collaboration between neuroscientists and researchers from diverse fields. Integrates expertise from psychology, sociology, and other disciplines to ensure a holistic approach.

Applications: Neurobiological Methodology, which is a descriptive methodology in research, holds immense potential across various research domains:

In Psychology: Unraveling the neural basis of psychological disorders, emotions, and cognitive functions.

In Marketing: Understanding consumer behavior by examining the neural responses to advertisements and product choices.

In Education: Enhancing learning methodologies by identifying neural patterns associated with effective teaching strategies.

Challenges and Future Directions: Despite its promises, Neurobiological Methodology faces challenges such as data complexity and ethical considerations. Future research should focus on refining methodologies, establishing ethical guidelines, and fostering interdisciplinary collaboration to unlock the full potential of this unexplored approach. Neurobiological Methodology emerges as a groundbreaking frontier, offering a novel lens through which researchers can delve into the intricacies of human cognition and behavior. As one of the different types of methodology in research, it holds the potential to reshape our understanding of the mind and pave the way for innovative solutions across diverse fields.

Methodology 2: Augmented Reality (AR) Research Methodology

Augmented Reality (AR) Research Methodology marks an unexplored frontier, intertwining cutting-edge AR technologies with traditional research methods. This is one of the types of methodology in research which seeks to create immersive environments for data collection, offering a unique perspective on human behavior and decision-making.

Constructs simulated environments using AR technology to observe and analyze real-time human behavior.

Enables researchers to study reactions and interactions in controlled yet dynamic settings.

Integrates AR-generated data collection points within physical spaces.

Facilitates the gathering of diverse data sets by embedding virtual elements in real-world contexts.

Utilizes AR interfaces to track user interactions and responses.

Enhances the understanding of user engagement and decision-making processes within augmented scenarios.

Combines AR experiences with traditional research methods such as exploratory research in research methodology for a comprehensive approach.

Allows researchers to triangulate findings by comparing results obtained from both virtual and non-virtual settings.

Applications: AR Research Methodology, which is also a descriptive methodology in research, holds promise across various research domains:

Simulating scenarios to observe human responses to environmental changes in descriptive qualitative research methodology.

Analyzing consumer behavior within augmented retail environments for product placement and advertising strategies.

Creating interactive learning experiences to study the impact of AR on knowledge retention.

Challenges and Future Directions: Challenges such as technological constraints and the need for standardized protocols highlight the evolving nature of this Research methodology types. Future endeavors should focus on refining AR applications, establishing ethical guidelines, and exploring collaborative opportunities with AR developers. Augmented Reality Research Methodology stands as an exciting avenue among the types of methodology in research, offering a transformative approach to understanding human behavior within virtual and augmented spaces. As technology continues to advance, this methodology holds the potential to redefine the landscape of research methodologies across diverse disciplines.

Methodology 3: Predictive Analytics in Social Sciences

Predictive Analytics in Social Sciences emerges as a groundbreaking methodology in research papers, introducing advanced statistical models and machine learning algorithms to forecast social trends and behaviors. This type of exploratory research methodologies harnesses the power of predictive analytics to offer a new dimension to traditional categories of research methodology.

Advanced Statistical Models:

Applies sophisticated statistical models, including regression analysis and time-series forecasting.

Enables researchers to identify patterns and relationships within social data.

Machine Learning Algorithms:

Integrates machine learning algorithms to predict future outcomes based on historical data.

Provides a dynamic and adaptive approach to understanding social phenomena in descriptive qualitative research methodology.

Big Data Utilization:

Harnesses large datasets from diverse sources, including social media, surveys, and public records.

Facilitates the identification of trends and correlations within complex social systems.

Real-Time Analysis:

Conducts real-time analysis of social data to generate instant predictions.

Allows for timely interventions and policy adjustments based on emerging social patterns.

Applications: Predictive Analytics in Social Sciences holds immense potential across various applications:

In Sociology: Forecasting demographic shifts, social movements, and cultural trends.

In Public Policy: Informing policy decisions by predicting the potential impact of interventions.

In Market Research: Anticipating consumer behavior and market trends for strategic planning.

Challenges and Future Directions: Despite its promises, integrating predictive analytics into social sciences faces challenges such as data privacy concerns and model interpretability, which is a type of exploratory research methodologies. Future research should focus on refining models, addressing ethical considerations, and enhancing the transparency of predictive analytics methodologies.

Predictive Analytics in Social Sciences stands as a dynamic methodology, extending beyond basic research methodology to offer foresight into the complex dynamics of human societies. As we embrace the era of big data, this approach holds the potential to revolutionize how we understand and respond to social changes in real time.

Methodology 4: Quantum Research Methodology

Quantum Research Methodology represents a paradigm shift, bridging the world of quantum physics with a basic research methodology. This unexplored approach challenges the traditional classification of research methodology by harnessing the principles of quantum mechanics for data analysis.

Quantum Computing for Data Processing: Utilizes quantum computing’s parallel processing capabilities for handling complex datasets. Offers a quantum leap in computational efficiency, enabling the analysis of vast amounts of information.

Quantum Entanglement in Data Relationships: Applies the concept of quantum entanglement to identify interconnected relationships within datasets. Provides a unique perspective on the interdependence of variables in comprehensive research methodology.

Superposition for Multifaceted Analysis: Exploits quantum superposition to analyze data simultaneously from multiple perspectives. Enhances researchers’ ability to examine complex phenomena from various angles.

Quantum Algorithms for Pattern Recognition: Develops quantum algorithms for advanced pattern recognition within datasets. Enables the identification of subtle patterns that may go unnoticed with classical algorithms.

Applications: Quantum Research Methodology holds potential classification of research methodology across diverse fields:

Exploring quantum phenomena and complex physical systems with enhanced computational power.

Analyzing intricate biological datasets to uncover hidden relationships and patterns.

Enhancing predictive modeling and risk analysis with quantum algorithms.

Challenges and Future Directions: The integration of quantum principles into research methodologies presents challenges such as the need for quantum expertise and the development of quantum-safe data encryption. Future research should focus on refining quantum algorithms, expanding interdisciplinary collaborations, and addressing ethical considerations. Quantum Research Methodology offers a novel and comprehensive approach that transcends traditional classifications of research methodology. As quantum technologies continue to advance, this unexplored frontier holds the promise of revolutionizing how we conduct research, analyze data, and gain insights into the underlying structures of complex systems.

Methodology 5: Bibliometric Research Methodology

Bibliometric research methodology is a quantitative approach that analyzes patterns and trends within academic literature, utilizing bibliographic data to gain insights into the scholarly landscape in the comprehensive research methodology.

Citation Analysis:

Examines the frequency and impact of citations to understand the influence of a publication.

Identifies seminal works and measures the academic impact of research.

Co-authorship Networks:

Maps collaborations among researchers through analysis of co-authored publications.

Unveils research communities and the dynamics of collaborative efforts.

Journal Impact Factors:

Evaluates the prestige and impact of academic journals based on citation patterns.

Assists researchers in identifying reputable outlets for publication.

Keyword Co-occurrence:

Identifies prevalent themes and topics within a field by analyzing the co-occurrence of keywords.

Facilitates trend analysis and the identification of emerging research areas.

Applications:

Research Evaluation:

Assessing the impact and productivity of researchers, institutions, or journals.

Informing funding agencies and policymakers in decision-making processes.

Trend Analysis:

Identifying emerging topics and research directions within a discipline.

Assisting researchers in staying abreast of the latest developments.

Collaboration Mapping:

Facilitating the identification of potential collaborators and research networks.

Enhancing interdisciplinary research initiatives.

Challenges:

Data Quality and Availability:

Limited availability and consistency of bibliographic data.

Challenges in obtaining accurate and comprehensive citation information.

Discipline-specific Differences:

Variability in citation practices across disciplines.

Difficulty in creating standardized metrics applicable to all fields.

Self-citation Bias:

Influence of self-citations on impact metrics.

Requires careful consideration to avoid skewing results.

Future Directions:

Integration with Altmetrics:

Incorporating alternative metrics like social media mentions to provide a more comprehensive assessment of research impact.

Open Science Initiatives:

Embracing open access principles to enhance data sharing and transparency.

Facilitating broader collaboration and increasing the accessibility of research outputs.

Machine Learning Applications:

Implementing machine learning algorithms for more sophisticated analysis.

Enhancing the automation of bibliometric processes and improving accuracy.

Final Thoughts

In wrapping up our exploration of the top 5 unexplored types of research methodology for 2024, it’s like we’ve discovered a treasure chest of new ideas. These methods are like a breath of fresh air in the world of research. From understanding how our brains work to creating virtual worlds with Augmented Reality, and predicting social trends, we’re on the brink of something big. 

Quantum research and Blockchain verification bring a touch of magic, making our data analysis smarter and more secure. These aren’t just fancy trends; they’re like keys to unlock a whole new era of learning. So, in 2024, researchers, buckle up and dive into these research methodology – the journey promises to be full of surprises, discoveries, and a whole lot of new knowledge!

Educba is a website that provides researchers with a comprehensive guide to different types of research methodologies. The website offers a wide range of courses and tutorials on research methodology, which can help researchers develop their research skills and knowledge. By taking these courses, researchers can learn about different research methods and techniques, such as surveys, case studies, and experiments. 

This knowledge can help researchers design and conduct their research more effectively and efficiently. Additionally, the website provides a platform for researchers to connect with other researchers and experts in their field. This can help researchers build their professional network and find new opportunities for research and collaboration. Overall, educba.com is a valuable resource for researchers who are looking to develop their research skills and knowledge and build their professional network.

Frequently Asked Questions

What is the research methodology?

Research methodology is the systematic process used to conduct and analyze research.

What is literature review in research methodology?

Literature review in research methodology involves reviewing and analyzing existing literature on a specific topic.

What is qualitative research methodology?

Qualitative research methodology involves exploring and understanding complex phenomena through non-numerical data.

What are qualitative methodologies?

Qualitative methodologies encompass various approaches like interviews, focus groups, and content analysis.

What are research methodology types?

Research methodology types include qualitative, quantitative, mixed methods, experimental, and survey research.

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Choosing the Right Research Methodology: A Guide for Researchers

• 3 minute read
• 47.2K views

Table of Contents

Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

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When Data Speak, Listen: Importance of Data Collection and Analysis Methods

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• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism. Run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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The Top 3 Types of Dissertation Research Explained

Preparing for your doctoral dissertation takes serious perseverance. You’ve endured years of studies and professional development to get to this point. After sleepless nights and labor-intensive research, you’re ready to present the culmination of all of your hard work. Even with a strong base knowledge, it can be difficult — even daunting — to decide how you will begin writing.

By taking a wide-lens view of the dissertation research process , you can best assess the work you have ahead of you and any gaps in your current research strategy. Subsequently, you’ll begin to develop a timeline so you can work efficiently and cross that finish line with your degree in hand.

What Is a Dissertation?

A dissertation is a published piece of research on a novel topic in your chosen field. Students complete a dissertation as part of a doctoral or PhD program. For most students, a dissertation is the first substantive piece of academic research they will write. 

Because a dissertation becomes a published piece of academic literature that other academics may cite, students must defend it in front of a board of experts consisting of peers in their field, including professors, their advisor, and other industry experts. 

For many students, a dissertation is the first piece of research in a long career full of research. As such, it’s important to choose a topic that’s interesting and engaging.

Types of Dissertation Research

Dissertations can take on many forms, based on research and methods of presentation in front of a committee board of academics and experts in the field. Here, we’ll focus on the three main types of dissertation research to get you one step closer to earning your doctoral degree.

1. Qualitative

The first type of dissertation is known as a qualitative dissertation . A qualitative dissertation mirrors the qualitative research that a doctoral candidate would conduct throughout their studies. This type of research relies on non-numbers-based data collected through things like interviews, focus groups and participant observation. 

The decision to model your dissertation research according to the qualitative method will depend largely on the data itself that you are collecting. For example, dissertation research in the field of education or psychology may lend itself to a qualitative approach, depending on the essence of research. Within a qualitative dissertation research model, a candidate may pursue one or more of the following:

• Case study research
• Autoethnographies
• Narrative research 
• Grounded theory 

Although individual approaches may vary, qualitative dissertations usually include certain foundational characteristics. For example, the type of research conducted to develop a qualitative dissertation often follows an emergent design, meaning that the content and research strategy changes over time. Candidates also rely on research paradigms to further strategize how best to collect and relay their findings. These include critical theory, constructivism and interpretivism, to name a few. 

Because qualitative researchers integrate non-numerical data, their methods of collection often include unstructured interview, focus groups and participant observations. Of course, researchers still need rubrics from which to assess the quality of their findings, even though they won’t be numbers-based. To do so, they subject the data collected to the following criteria: dependability, transferability and validity. 

When it comes time to present their findings, doctoral candidates who produce qualitative dissertation research have several options. Some choose to include case studies, personal findings, narratives, observations and abstracts. Their presentation focuses on theoretical insights based on relevant data points. 

2. Quantitative

Quantitative dissertation research, on the other hand, focuses on the numbers. Candidates employ quantitative research methods to aggregate data that can be easily categorized and analyzed. In addition to traditional statistical analysis, quantitative research also hones specific research strategy based on the type of research questions. Quantitative candidates may also employ theory-driven research, replication-based studies and data-driven dissertations. 

When conducting research, some candidates who rely on quantitative measures focus their work on testing existing theories, while others create an original approach. To refine their approach, quantitative researchers focus on positivist or post-positivist research paradigms. Quantitative research designs focus on descriptive, experimental or relationship-based designs, to name a few. 

To collect the data itself, researchers focus on questionnaires and surveys, structured interviews and observations, data sets and laboratory-based methods. Then, once it’s time to assess the quality of the data, quantitative researchers measure their results against a set of criteria, including: reliability, internal/external validity and construct validity. Quantitative researchers have options when presenting their findings. Candidates convey their results using graphs, data, tables and analytical statements.

3. Mixed-Method

Many PhD candidates also use a hybrid model in which they employ both qualitative and quantitative methods of research. Mixed dissertation research models are fairly new and gaining traction. For a variety of reasons, a mixed-method approach offers candidates both versatility and credibility. It’s a more comprehensive strategy that allows for a wider capture of data with a wide range of presentation optimization. 

In the most common cases, candidates will first use quantitative methods to collect and categorize their data. Then, they’ll rely on qualitative methods to analyze that data and draw meaningful conclusions to relay to their committee panel. 

With a mixed-method approach, although you’re able to collect and analyze a more broad range of data, you run the risk of widening the scope of your dissertation research so much that you’re not able to reach succinct, sustainable conclusions. This is where it becomes critical to outline your research goals and strategy early on in the dissertation process so that the techniques you use to capture data have been thoroughly examined. 

How to Choose a Type of Dissertation Research That’s Right for You

After this overview of application and function, you may still be wondering how to go about choosing a dissertation type that’s right for you and your research proposition. In doing so, you’ll have a couple of things to consider: 

• What are your personal motivations? 
• What are your academic goals? 

It’s important to discern exactly what you hope to get out of your doctoral program . Of course, the presentation of your dissertation is, formally speaking, the pinnacle of your research. However, doctoral candidates must also consider:

• Which contributions they will make to the field
• Who they hope to collaborate with throughout their studies
• What they hope to take away from the experience personally, professionally and academically

Personal Considerations

To discern which type of dissertation research to choose, you have to take a closer look at your learning style, work ethic and even your personality. 

Quantitative research tends to be sequential and patterned-oriented. Steps move in a logical order, so it becomes clear what the next step should be at all times. For most candidates, this makes it easier to devise a timeline and stay on track. It also keeps you from getting overwhelmed by the magnitude of research involved. You’ll be able to assess your progress and make simple adjustments to stay on target. 

On the other hand, maybe you know that your research will involve many interviews and focus groups. You anticipate that you’ll have to coordinate participants’ schedules, and this will require some flexibility. Instead of creating a rigid schedule from the get-go, allowing your research to flow in a non-linear fashion may actually help you accomplish tasks more efficiently, albeit out of order. This also allows you the personal versatility of rerouting research strategy as you collect new data that leads you down other paths. 

After examining the research you need to conduct, consider more broadly: What type of student and researcher are you? In other words, What motivates you to do your best work? 

You’ll need to make sure that your methodology is conducive to the data you’re collecting, and you also need to make sure that it aligns with your work ethic so you set yourself up for success. If jumping from one task to another will cause you extra stress, but planning ahead puts you at ease, a quantitative research method may be best, assuming the type of research allows for this. 

Professional Considerations

The skills you master while working on your dissertation will serve you well beyond the day you earn your degree. Take into account the skills you’d like to develop for your academic and professional future. In addition to the hard skills you will develop in your area of expertise, you’ll also develop soft skills that are transferable to nearly any professional or academic setting. Perhaps you want to hone your ability to strategize a timeline, gather data efficiently or draw clear conclusions about the significance of your data collection. 

If you have considerable experience with quantitative analysis, but lack an extensive qualitative research portfolio, now may be your opportunity to explore — as long as you’re willing to put in the legwork to refine your skills or work closely with your mentor to develop a strategy together. 

Academic Considerations

For many doctoral candidates who hope to pursue a professional career in the world of academia, writing your dissertation is a practice in developing general research strategies that can be applied to any academic project. 

Candidates who are unsure which dissertation type best suits their research should consider whether they will take a philosophical or theoretical approach or come up with a thesis that addresses a specific problem or idea. Narrowing down this approach can sometimes happen even before the research begins. Other times, candidates begin to refine their methods once the data begins to tell a more concrete story.

Next Step: Structuring Your Dissertation Research Schedule

Once you’ve chosen which type of dissertation research you’ll pursue, you’ve already crossed the first hurdle. The next hurdle becomes when and where to fit dedicated research time and visits with your mentor into your schedule. The busyness of day-to-day life shouldn’t prevent you from making your academic dream a reality. In fact, search for programs that assist, not impede, your path to higher levels of academic success. 

Find out more about SNU’s online and on-campus education opportunities so that no matter where you are in life, you can choose the path that’s right for you.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Methodology Used for PhD Research

Common methods used in social science research.

Doctoral research is among the highest level of academic research conducted in universities and institutes throughout the United States. The methods used to conduct Ph.D. research should be sound and the data that results from the research must be credible. Scientific methodologies have been created to ensure the soundness and credibility of doctoral research and to secure continuity in research results. Among the most often employed methodologies are quantitative methods, qualitative methods, comparative methods and clinical trials.

Qualitative Research

Qualitative research methodologies are those scientific approaches that attempt to give meaning to certain experiences by describing cultural phenomena, human behavior or belief systems. Qualitative research is conducted by interviewing people, using a combination of closed and open-ended questions and analyzing the responses to draw conclusions about a pattern of behavior or social phenomena. One example of qualitative research in the field of cognitive learning is obtaining information about students' learning styles by listening to their own subjective descriptions of how they learn.

Quantitative Research

Quantitative research methodology is conducted by collecting data and creating statistics based on the evidence collected to prove or disprove a hypothesis. Quantitative research uses questionnaires or surveys of individuals and compiles the results into a chart, graph or other type of report. Quantitative research is useful in evaluating attitudes or views on certain topics. For example, doctoral research in the field of political science could survey whether people would support a government policy regarding taxes on luxury goods to shed light on the viability of such a proposal in a given community.

Comparative Research

The comparative research approach seeks to draw parallels and contrasts between two similar or competing systems of thought, among several cultures or within cross-cultural societies. Comparative research methodology is carried out by using a variety of tools, including surveys, personal observation and analysis of national data. Comparative research is useful for classifying shared social phenomena, placing cultural values in context and analyzing cultural differences. A doctoral project in criminal law could use comparative research, for example, to study how various countries in the European Union approach the rehabilitation of convicted criminals.

Clinical Trials

In the field of medicine and biological sciences, clinical trials are the methodology of choice. They are laboratory experiments carried out to test, confirm or disprove scientific theories or to measure the effect of medication or treatment on animals or humans. Clinical trials are conducted by observing the response of certain individuals to medical interventions and comparing those responses to individuals who have not received such medical interventions. In doctoral research in the field of physical therapy, clinical trials are an effective methodology for gauging the effects of therapeutic devices in patients.

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• University of Surrey: Comparative Research Methods

Trudie Longren began writing in 2008 for legal publications, including the "American Journal of Criminal Law." She has served as a classroom teacher and legal writing professor. Longren holds a bachelor's degree in international politics, a Juris Doctor and an LL.M. in human rights. She also speaks Spanish and French.

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Research Methods for Dissertation – Types with Comparison

Published by Carmen Troy at August 13th, 2021 , Revised On June 14, 2023

Introduction

“Research methods for a dissertation refer to the specific approaches, procedures, and techniques employed by researchers to investigate and gather data for their dissertation projects.”

These methods provide a systematic and structured framework for conducting research, ensuring the reliability, validity, and rigour of the study.

What are the different research methods for the dissertation, and which one should I use?

Choosing the right research method for a dissertation is a grinding and perplexing aspect of the dissertation research process. A well-defined  research methodology  helps you conduct your research in the right direction, validates the  results  of your research, and makes sure that the study you’re conducting answers the set  research questions .

The research  title,  research questions,  hypothesis , objectives, and study area generally determine the best research method in the dissertation.

This post’s primary purpose is to highlight what these different  types of research  methods involve and how you should decide which type of research fits the bill. As you read through this article, think about which one of these research methods will be the most appropriate for your research.

The practical, personal, and academic reasons for choosing any particular method of research are also analysed. You will find our explanation of experimental , descriptive , historical , quantitative , qualitative , and mixed research methods useful regardless of your field of study.

While choosing the right method of research for your own research, you need to:

• Understand the difference between research methods and  methodology .
• Think about your research topic, research questions, and research objectives to make an intelligent decision.
• Know about various types of research methods so that you can choose the most suitable and convenient method as per your research requirements.

Research Methodology Vs. Research Methods

A well-defined  research methodology  helps you conduct your research in the right direction, validates the  results  of your research, and makes sure that the study you are conducting answers the set  research questions .

Research methods are the techniques and procedures used for conducting research. Choosing the right research method for your writing is an important aspect of the  research process .

You need to either collect data or talk to the people while conducting any research. The research methods can be classified based on this distinction.

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Types of Research Methods

Research methods are broadly divided into six main categories.

Experimental Research Methods

Descriptive research methods, historical research methods, quantitative research methods, qualitative research methods, mixed methods of research.

Experimental research  includes the experiments conducted in the laboratory or observation under controlled conditions. Researchers try to study human behavior by performing various experiments. Experiments can vary from personal and informal natural comparisons. It includes three  types of variables;

• Independent variable
• Dependent variable
• Controlled variable

Types of Experimental Methods

Laboratory experiments

The experiments were conducted in the laboratory. Researchers have control over the variables of the experiment.

Field experiment

The experiments were conducted in the open field and environment of the participants by incorporating a few artificial changes. Researchers do not have control over variables under measurement. Participants know that they are taking part in the experiment.

Natural experiments

The experiment is conducted in the natural environment of the participants. The participants are generally not informed about the experiment being conducted on them.

Example : Estimating the health condition of the population.

Quasi-experiments

A quasi-experiment is an experiment that takes advantage of natural occurrences. Researchers cannot assign random participants to groups.

Example: Comparing the academic performance of the two schools.

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Descriptive research aims at collecting the information to answer the current affairs. It follows the Ex post facto research, which predicts the possible reasons behind the situation that has already occurred. It aims to answer questions like how, what, when, where, and what rather than ‘why.’

In  historical research , an investigator collects, analyses the information to understand, describe, and explain the events that occurred in the past. Researchers try to find out what happened exactly during a certain period of time as accurately and as closely as possible. It does not allow any manipulation or control of variables.

Quantitative research  is associated with numerical data or data that can be measured. It is used to study a large group of population. The information is gathered by performing statistical, mathematical, or computational techniques.

Quantitative research isn’t simply based on  statistical analysis or quantitative techniques but rather uses a certain approach to theory to address research hypotheses or research questions, establish an appropriate research methodology, and draw findings &  conclusions .

Some most commonly employed quantitative research strategies include data-driven dissertations, theory-driven studies, and reflection-driven research. Regardless of the chosen approach, there are some common quantitative research features as listed below.

• Quantitative research is based on testing or building on existing theories proposed by other researchers whilst taking a reflective or extensive route.
• Quantitative research aims to test the research hypothesis or answer established research questions.
• It is primarily justified by positivist or post-positivist research paradigms.
• The  research design can be relationship-based, quasi-experimental, experimental, or descriptive.
• It draws on a small sample to make generalisations to a wider population using probability sampling techniques.
• Quantitative data is gathered according to the established research questions and using research vehicles such as structured observation, structured interviews, surveys, questionnaires, and laboratory results.
• The researcher uses  statistical analysis  tools and techniques to measure variables and gather inferential or descriptive data. In some cases, your tutor or members of the dissertation committee might find it easier to verify your study results with numbers and statistical analysis.
• The accuracy of the study results is based on external and internal validity and the authenticity of the data used.
• Quantitative research answers research questions or tests the hypothesis using charts, graphs, tables, data, and statements.
• It underpins  research questions  or hypotheses and findings to make conclusions.
• The researcher can provide recommendations for future research and expand or test existing theories.

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It is a type of scientific research where a researcher collects evidence to seek answers to a  question . It is associated with studying human behaviour from an informative perspective. It aims at obtaining in-depth details of the problem.

As the term suggests,  qualitative research  is based on qualitative research methods, including participants’ observations, focus groups, and unstructured interviews.

Qualitative research is very different in nature when compared to quantitative research. It takes an established path towards the  research process , how  research questions  are set up, how existing theories are built upon, what research methods are employed, and how the  findings  are unveiled to the readers.

You may adopt conventional methods, including phenomenological research, narrative-based research, grounded theory research,  ethnographies ,  case studies , and auto-ethnographies.

Again, regardless of the chosen approach to qualitative research, your dissertation will have unique key features as listed below.

• The research questions that you aim to answer will expand or even change as the  dissertation writing process continues. This aspect of the research is typically known as an emergent design where the research objectives evolve with time.
• Qualitative research may use existing theories to cultivate new theoretical understandings or fall back on existing theories to support the research process. However, the original goal of testing a certain theoretical understanding remains the same.
• It can be based on various research models, such as critical theory, constructivism, and interpretivism.
• The chosen research design largely influences the analysis and discussion of results and the choices you make. Research design depends on the adopted research path: phenomenological research, narrative-based research, grounded theory-based research, ethnography, case study-based research, or auto-ethnography.
• Qualitative research answers research questions with theoretical sampling, where data gathered from an organisation or people are studied.
• It involves various research methods to gather qualitative data from participants belonging to the field of study. As indicated previously, some of the most notable qualitative research methods include participant observation, focus groups, and unstructured  interviews .
• It incorporates an  inductive process where the researcher analyses and understands the data through his own eyes and judgments to identify concepts and themes that comprehensively depict the researched material.
• The key quality characteristics of qualitative research are transferability, conformity, confirmability, and reliability.
• Results and discussions are largely based on narratives, case study and personal experiences, which help detect inconsistencies, observations, processes, and ideas.s
• Qualitative research discusses theoretical concepts obtained from the results whilst taking research questions and/or hypotheses  to draw general  conclusions .

Now that you know the unique differences between quantitative and qualitative research methods, you may want to learn a bit about primary and secondary research methods.

Here is an article that will help you  distinguish between primary and secondary research and decide whether you need to use quantitative and/or qualitative primary research methods in your dissertation.

Alternatively, you can base your dissertation on secondary research, which is descriptive and explanatory in essence.

Types of Qualitative Research Methods

Action research

Action research  aims at finding an immediate solution to a problem. The researchers can also act as the participants of the research. It is used in the educational field.

A  case study  includes data collection from multiple sources over time. It is widely used in social sciences to study the underlying information, organisation, community, or event. It does not provide any solution to the problem. Researchers cannot act as the participants of the research.

Ethnography

In  this type of research, the researcher examines the people in their natural environment. Ethnographers spend time with people to study people and their culture closely. They can consult the literature before conducting the study.

When you combine quantitative and qualitative methods of research, the resulting approach becomes mixed methods of research.

Over the last few decades, much of the research in academia has been conducted using mixed methods because of the greater legitimacy this particular technique has gained for several reasons including the feeling that combining the two types of research can provide holistic and more dependable results.

Here is what mixed methods of research involve:

• Interpreting and investigating the information gathered through quantitative and qualitative techniques.
• There could be more than one stage of research. Depending on the research topic, occasionally it would be more appropriate to perform qualitative research in the first stage to figure out and investigate a problem to unveil key themes; and conduct quantitative research in stage two of the process for measuring relationships between the themes.

Note: However, this method has one prominent limitation, which is, as previously mentioned, combining qualitative and quantitative research can be difficult because they both are different in terms of design and approach. In many ways, they are contrasting styles of research, and so care must be exercised when basing your dissertation on mixed methods of research.

When choosing a research method for your own dissertation, it would make sense to carefully think about your  research topic ,  research questions , and research objectives to make an intelligent decision in terms of the philosophy of  research design .

Dissertations based on mixed methods of research can be the hardest to tackle even for PhD students.

Our writers have years of experience in writing flawless and to the point mixed methods-based dissertations to be confident that the dissertation they write for you will be according to the technical requirements and the formatting guidelines.

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Please Find Below an Example of Research Methods Section in a Dissertation or Thesis.

Background and Problem

Diversity management became prominent in the late twentieth century, with foundations in America. Historically homogeneous or nondiverse nations, such as Finland, have not yet experienced the issues associated with rising cultural and ethnic diversity in the workforce. Regardless of the environment, workforce diversity garners greater attention and is characterised by its expanding relevance due to globalised and international companies, global and national worker mobility, demographic shifts, or enhancing productivity.

As a result, challenges of diversity management have been handled through legal, financial, and moral pressures (Hayes et al., 2020). The evolving structure of the working population in terms of language, ethnic background, maturity level, faith, or ethnocultural history is said to pose a challenge to human resource management (HRM) in utilising diversity: the understanding, abilities, and expertise prospects of the entire workforce to deal with possible developments.

The European approach to diversity management is regarded as growing. However, it is found to emphasise the relationship to business and lack competence in diversity management problems. Mass immigration concentrates variety, sometimes treated as cultural minority issues, implying the normalisation of anti-discrimination actions (Yadav and Lenka, 2020).

These causes, in turn, have provided the basis of comprehensive diversity research, which has generated different theories, frameworks, concepts, and guidelines from interdisciplinary viewpoints, such as industrial and organisational psychology and behaviour (OB), cultural studies, anthropology, migration, economics, postcolonialism, and so on. And in the form of international, social and cultural, organisational, group, and individual scale diversity analysis. This dissertation focuses on diversity concerns from impression management, specifically from HRM as an executive-level phenomenon (Seliverstova, 2021).

As conceptual frameworks, organisational structures concentrating on the production of diversity and social psychology, notably social identity theory with diverse ‘identities’ of persons or intergroup connections, are primarily employed. The study’s primary goal in the workplace is to discover inequities or examine the effects of diversity on workplace outcomes.

Individual study interests include behaviours, emotions, intelligence, intercultural skills or competencies, while group research interests include group dynamics, intergroup interactions, effectiveness, and cooperation or collaboration. Organisational studies address themes such as workforce composition, workplace equality, and diversity challenges and how they may be managed accordingly. Domestic diversity, omitting national distinctions, or global diversity, about diverse country cultures, might be studied further (AYDIN and ÖZEREN, 2018).

Diversity is a context-dependent, particular, comparative, complicated, plural phrase or idea with varying interpretations in different organisations and cultures and no unified definition. As a result, in addition to many internal and external elements, diversity may be managed, individuals taught, and organisations have grown in various ways. This dissertation considers diversity in an organisational environment as a construct of ‘differences’ to be handled (Cummings, 2018).

Various management systems have grown in stages, bringing diverse diversity management concepts. Equality/equal opportunities (EO) legislation and diversity management are the two conventional approaches and primary streams with differing theoretical foundations for managing and dealing with workforce diversity challenges (DM).

These approaches relate to whether diversity is handled by increasing sameness by legal pressures or by voluntarily respecting people’s differences, which shows an organisation’s responsiveness and proactivity toward managing diversity. But most of the literature in this area has avoided the impression management theories (Coad and Guenther, 2014). Therefore, this study will add a new dimension in this area by introducing impression management analysis.

Research Aim and Objectives

This research aims to analyse the impact of organisational structure on human resources diversification from the viewpoint of impression managerial theory. It has the following objectives:

• It will examine the existing impression management literature to draw insights into the relationship under consideration.
• It will identify various factors such as competency, social inclusion, etc., affecting the management’s decision to recruit diverse human resources.
• It will recommend appropriate organisational structures and HR policies to improve diversification of HR by reviewing impression management theories.

Research Questions

This research will answer the following questions:

• How does organisational structure affect human resources diversification from the viewpoint of impression managerial theory?
• What factors such as competency, social inclusion, etc., affect the management decision to recruit diverse human resources?
• What are appropriate organisational structures and HR policies to improve diversification of HR by reviewing impression management theories?

Research Hypothesis

The organisational structure significantly impacts the recruitment of diverse human resources.

Literature Review

According to Staniec and Zakrzewska-Bielawska (2010), considering strategy-oriented activities and organisational components are the critical foundation in the organisational structure required to align structure strategy. Each company’s internal organisation is somewhat distinctive, resulting from various corporate initiatives and historical conditions.

Furthermore, each design is based on essential success elements and vital tasks inherent in the firm plan. This article offers empirical research on unique organisational structure elements in Polish firms in the context of concentration and diversification tactics. And companies that adopted concentration techniques mainly used functional organisational structures.

Tasks were primarily classified and categorised based on functions and phases of the technical process, with coordination based on hierarchy. Jobs were also highly centralised and formalised. Organisational structures of an active type were also prevalent in many firms. Only a handful of the evaluated organisations possessed flexible contemporary divisional or matrix structures appropriate to differentiation. However, it appears that even such organisations should adjust their organisational solutions to perform successfully in an immensely complex and chaotic environment.

Similarly, according to Yang and Konrad (2011), diversity management techniques are the institutionalised methods created and applied by organisations to manage diversity among all organisational shareholders. They examined the existing research on the causes and significance of diversity management approaches.

They construct a research model indicating many potential routes for future study using institutional and resource-based theories. They also offer prospective avenues for study on diversity management techniques to further the two theoretical viewpoints. The findings indicate that research on diverse management practises might provide perceptions into the two ideologies. Diversity management provides a method for reconciling the agency vs structure issue for institutional concept.

Furthermore, diversity management is a suitable framework for studying how institutional pressures are translated into organisational action and the relationship between complying with institutional mandates and attaining high performance. Research on diversity management raises the importance of environmental normative elements in resource-based reasoning.

It allows for exploring essential resource sources and the co-evolution of diversity resources and management capacities, potentially developing dynamic resource-based theory. Furthermore, a review of the existing research on diversity management practices reveals that research in this field has nearly entirely concentrated on employee-related activities.

However, in establishing the idea of diversity management practises, we included the practises that companies put in place to manage diversity across all stakeholder groups on purpose. Management techniques for engaging with consumers, dealers, supervisors, board directors, and community members are critical for meeting institutional theory’s social and normative commitments.

Moreover, according to Sippola (2014), this research looks at diversity management from the standpoint of HRM. The study aims to discover the effects of expanding workforce diversity on HRM inside firms. This goal will be accomplished through four papers examining diversity management’s impacts on HRM from various viewpoints and mostly in longitudinal contexts.

The purpose of the first article, as a pilot survey, is to determine the reasons, advantages, and problems of rising cultural diversity and the consequences for HRM to get a preliminary grasp of the issue in the specific setting. According to the report, diversity is vital for productivity but is not often emphasised in HRM strategy.

The key areas that were changed were acquisition, development, and growth. The second article examines how different diversity management paradigms recognised in businesses affect HRM. It offers an experimentally verified typology that explains reactive or proactive strategic and operational level HRM activities in light of four alternative diversity management perspectives.

The third essay will examine how a ‘working culture bridge group’ strategy fosters and enhances workplace diversity. The research looks into how development goals are defined, what training and development techniques are used, and the consequences and causal factors when an analysis measures the training and development approach.

The primary goal of article four is to establish which components of diversity management design are globally integrated into multinational corporations (MNCs) and which integrating (delivery) methods are employed to facilitate it. Another goal is to identify the institutional problems faced by the Finnish national diversity setting during the integration process.

The findings show that the example organisation achieved more excellent global uniformity at the level of diversification concept through effective use of multiple frameworks but was forced to rely on a more multinational approach to implementing diversification policies and procedures. The difficulties faced emphasised the distinctiveness of Finland’s cognitive and normative institutional setting for diversity.

Furthermore, according to Guillaume et al. (2017), to compensate for the dual-edged character of demographic workplace diversity impacts on social inclusion, competence, and well-being-related factors, research has shifted away from straightforward main effect methods and begun to investigate factors that moderate these effects.

While there is no shortage of primary research on the circumstances that lead to favourable or poor results, it is unknown which contextual elements make it work. Using the Classification framework as a theoretical lens, they examine variables that moderate the impacts of workplace diversity on social integration, performance, and well-being outcomes, emphasising characteristics that organisations and managers can influence.

They suggest future study directions and end with practical applications. They concluded that faultlines, cross-categorisation, and status variations across demographic groupings highlight variety. Cross-categorisation has been proven to reduce intergroup prejudice while promoting social inclusion, competence, and well-being. Whether faultlines and subgroup status inequalities promote negative or good intergroup interactions and hinder social integration, performance, and well-being depends on whether situational factors encourage negative or positive intergroup connections. The impacts were not mitigated by team size or diversity type.

Furthermore, our data demonstrate that task characteristics are essential for workgroup diversity. Any demographic diversity in workgroups can promote creativity, but only when combined with task-relevant expertise improves the performance of teams undertaking complicated tasks. The type of team and the industrial context do not appear to play an effect. It is unclear if these findings apply to relational demography and organisational diversity impacts. There is some evidence that, under some settings, relational demography may increase creativity, and, as previously said, demographic variety may help firms function in growth-oriented strategy contexts.

Likewise, according to Ali, Tawfeq, and Dler (2020), diversity management refers to organisational strategies that strive to increase the integration of people from diverse backgrounds into the framework of corporate goals. Organisations should develop productive ways to implement diversity management (DM) policies to establish a creative enterprise that can enhance their operations, goods, and services.

Furthermore, human resource management HRM is a clever tool for any firm to manage resources within the company. As a result, this article explores the link between DM, HR policies, and workers’ creative work-related behaviours in firms in Kurdistan’s Fayoum city. According to the questionnaire, two hypotheses were tested: the influence of HRM on diversity management, HRM on innovation, and the impact of diversity management on innovation.

The first premise is that workplace diversity changes the nature of working relationships, how supervisors and managers connect, and how workers respond to one another. It also addresses human resource functions such as record-keeping, training, recruiting, and employee competence needs. The last premise on the influence of diversity management on innovation is that workplace diversity assists a business in hiring a diverse range of personnel.

In other words, a vibrant population need individuals of varied personalities. Workplace diversity refers to a company’s workforce consisting of employees of various genders, ages, faiths, races, ethnicities, cultural backgrounds, religions, dialects, training, capabilities, etc. According to the study’s findings, human resource management strategies have a substantial influence on diversity management.

Second, diversity management was found to have a considerable impact on creativity. Finally, human resource management techniques influenced innovation significantly. Based on the findings, it was discovered that diversity management had a more significant influence on creation than human resource management.

Lastly, according to Li et al. (2021), the universal trend of rising workplace age diversity has increased the study focus on the organisational effects of age-diverse workforces. Prior research has mainly concentrated on the statistical association between age diversity and organisational success rather than experimentally examining the probable processes behind this relationship.

They argue that age diversity influences organisational performance through human and social capital using an intellectual capital paradigm. Moreover, they investigate workplace functional diversity and age-inclusive management as two confounding factors affecting the benefits of age diversity on physical and human capital.

Their hypotheses were evaluated using data from the Association for Human Resource Management’s major manager-reported workplace survey. Age diversity was favourably linked with organisational performance via the mediation of higher human and social capital. Furthermore, functional diversity and age-inclusive management exacerbated the favourable benefits of age variety on human and social capital. Their study gives insight into how age-diverse workforces might generate value by nurturing knowledge-based organisational resources.

Research Gap/ Contribution

Although there is a vast body of research in diversity in the human resource management area, many researchers explored various dimensions. But no study explicitly discovers the impact of organisational culture on human resource diversification. Moreover, no researchers examined the scope of impression management in this context.

Therefore, this research will fill this considerable literature gap by finding the direct impact of organisational structure on human resource diversification. Secondly, by introducing a new dimension of impression management theory. It will open new avenues for research in this area, and it will help HR managers to formulate better policies for a more inclusive organisational structure.

Research Methodology

It will be mixed quantitative and qualitative research based on the secondary data collected through different research journals and case studies of various companies. Firstly, the quantitative analysis will be conducted through a regression analysis to show the organisational structure’s impact on human resource diversification.

The dummy variable will be used to show organisational structure, and diversification will be captured through the ethnic backgrounds of the employees. Moreover, different variables will be added to the model, such as competency, social inclusion, etc. It will fulfil the objective of identifying various factors which affect the management decision to recruit diverse human resources. Secondly, a systematic review of the literature will be conducted for qualitative analysis to add the impression management dimension to the research. Google Scholar, JSTOR, Scopus, etc., will be used to search keywords such as human resource diversity, impression management, and organisation structure.

Research Limitation

Although research offers a comprehensive empirical analysis on the relationship under consideration due to lack of resources, the study is limited to secondary data. It would be better if the research would’ve been conducted on the primary data collected through the organisations. That would’ve captured the actual views of the working professionals. It would’ve increased the validity of the research.

Ali, M., Tawfeq, A., & Dler, S. (2020). Relationship between Diversity Management and Human Resource Management: Their Effects on Employee Innovation in the Organizations. Black Sea Journal of Management and Marketing, 1 (2), 36-44.

AYDIN, E., & ÖZEREN, E. (2018). Rethinking workforce diversity research through critical perspectives: emerging patterns and research agenda. Business & Management Studies: An International Journal, 6 (3), 650-670.

Coad, A., & Guenther, C. (2014). Processes of firm growth and diversification: theory and evidence. Small Business Economics, 43 (4), 857-871.

Cummings, V. (2018). Economic Diversification and Empowerment of Local Human Resources: Could Singapore Be a Model for the GCC Countries?. In. Economic Diversification in the Gulf Region, II , 241-260.

Guillaume, Y., Dawson, J., Otaye‐Ebede, L., Woods, S., & West, M. (2017). Harnessing demographic differences in organizations: What moderates the effects of workplace diversity? Journal of Organizational Behavior, 38 (2), 276-303.

Hayes, T., Oltman, K., Kaylor, L., & Belgudri, A. (2020). How leaders can become more committed to diversity management. Consulting Psychology Journal: Practice and Research, 72 (4), 247.

Li, Y., Gong, Y., Burmeister, A., Wang, M., Alterman, V., Alonso, A., & Robinson, S. (2021). Leveraging age diversity for organizational performance: An intellectual capital perspective. Journal of Applied Psychology, 106 (1), 71.

Seliverstova, Y. (2021). Workforce diversity management: a systematic literature review. Strategic Management, 26 (2), 3-11.

Sippola, A. (2014). Essays on human resource management perspectives on diversity management. Vaasan yliopisto.

Staniec, I., & Zakrzewska-Bielawska, A. (2010). Organizational structure in the view of single business concentration and diversification strategies—empirical study results. Recent advances in management, marketing, finances. WSEAS Press, Penang, Malaysia .

Yadav, S., & Lenka, U. (2020). Diversity management: a systematic review. Equality, Diversity and Inclusion: An International Journal .

Yang, Y., & Konrad, A. (2011). Understanding diversity management practices: Implications of institutional theory and resource-based theory. Group & Organization Management, 36 (1), 6-38.

FAQs About Research Methods for Dissertations

What is the difference between research methodology and research methods.

Research methodology helps you conduct your research in the right direction, validates the results of your research and makes sure that the study you are conducting answers the set research questions.

Research methods are the techniques and procedures used for conducting research. Choosing the right research method for your writing is an important aspect of the research process.

What are the types of research methods?

The types of research methods include:

•     Experimental research methods.
•     Descriptive research methods
•     Historical Research methods

What is a quantitative research method?

Quantitative research is associated with numerical data or data that can be measured. It is used to study a large group of population. The information is gathered by performing statistical, mathematical, or computational techniques.

What is a qualitative research method?

It is a type of scientific research where a researcher collects evidence to seek answers to a question . It is associated with studying human behavior from an informative perspective. It aims at obtaining in-depth details of the problem.

What is meant by mixed methods research?

Mixed methods of research involve:

• There could be more than one stage of research. Depending on the research topic, occasionally, it would be more appropriate to perform qualitative research in the first stage to figure out and investigate a problem to unveil key themes; and conduct quantitative research in stage two of the process for measuring relationships between the themes.

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What are the different research strategies you can use in your dissertation? Here are some guidelines to help you choose a research strategy that would make your research more credible.

A meta-analysis is a formal, epidemiological, quantitative study design that uses statistical methods to generalise the findings of the selected independent studies.

In correlational research, a researcher measures the relationship between two or more variables or sets of scores without having control over the variables.

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Ultimate Guide to the 7 Types of Research: Definitions, Examples, Advantages and Limitations!

About the article : different types of research.

Research is a fundamental aspect of any field of study, providing a systematic approach to gather and analyze information. It plays a crucial role in expanding knowledge, solving problems, and making informed decisions. Understanding the different types of research is essential for researchers to choose the most appropriate method for their study.

In this article, we will explore the various types of research methods commonly used in academic and professional settings. Each type of research has its own unique characteristics, strengths, and limitations. By gaining a comprehensive understanding of these research types, researchers can effectively design and conduct their studies to achieve their objectives.

Exploratory Research

Exploratory research is a type of research that is used to investigate a problem that is not clearly defined and gain a better understanding of the existing problem. It is often conducted when a researcher has just begun an investigation and wishes to understand the topic generally.

There are two main methods of conducting exploratory research: primary research and secondary research. Primary research involves collecting new data directly from the source, while secondary research involves analyzing existing data that has already been collected by others.

Under these two broad types, various methods can be employed to gather information. These methods include surveys, interviews , focus groups, observations, and case studies. Each method has its own advantages and disadvantages, and the choice of method depends on the nature of the research question and the available resources.

Exploratory research is valuable because it helps researchers gain insights and generate hypotheses for further investigation. It allows them to explore new areas of study and discover potential relationships between variables. However, it is important to note that exploratory research does not provide definitive answers or conclusive results. Instead, it lays the foundation for more in-depth research and helps researchers refine their research questions and methodologies.

Descriptive Research

Descriptive research is a methodological approach that seeks to depict the characteristics of a phenomenon or subject under investigation. It involves observing and measuring without manipulating variables, allowing researchers to identify characteristics, trends, and correlations. The main goal of descriptive research is to provide a detailed description of the population or phenomenon being studied. This type of research focuses on answering questions such as how, what, when, and where.

There are three basic approaches for gathering data in descriptive research: observational, case study, and survey. Observational research involves observing and recording behavior in its natural setting. Case study research involves in-depth analysis of a single individual, group, or situation. Survey research involves collecting data from a sample of individuals through questionnaires or interviews.

Descriptive research is particularly useful when researchers want to describe specific behaviors, characteristics, or trends as they occur in the environment. It provides a foundation for further research and can help generate hypotheses for future studies.

However, one limitation of descriptive research is that it does not establish causal relationships between variables. It can only provide a snapshot of the current state of the population or phenomenon being studied. Despite this limitation, descriptive research plays a crucial role in understanding and describing various aspects of the world around us.

Experimental Research

Experimental research is a quantitative research method with a scientific approach. It is the most familiar type of research design for individuals in the physical sciences and a host of other fields. This type of research design is popular in scientific experiments, social sciences, medical science, etc. Experimental research involves manipulating one or more variables to observe the effect on another variable. It aims to establish cause-and-effect relationships between variables. The researcher carefully controls and manipulates the independent variable(s) while measuring the dependent variable(s).

There are two broad categories of experimental research designs: true experimental designs and quasi-experimental designs. True experimental designs involve random assignment of participants to different groups and manipulation of the independent variable. Quasi-experimental designs lack random assignment but still involve manipulation of the independent variable.

One advantage of experimental research is its ability to establish causal relationships. By manipulating variables and controlling extraneous factors, researchers can determine whether changes in the independent variable(s) cause changes in the dependent variable(s). This allows for a more confident understanding of cause and effect.

Another advantage of experimental research is its versatility. It can be used in various fields and disciplines, allowing researchers to investigate a wide range of phenomena. Whether it’s testing the effectiveness of a new drug, studying the impact of different teaching methods, or exploring the relationship between variables, experimental research provides a powerful tool for scientific inquiry.

However, experimental research also has some limitations. One limitation is the potential for artificiality. In a controlled laboratory setting, variables may be manipulated in a way that does not fully reflect real-world conditions. This can limit the generalizability of the findings to real-life situations. Additionally, experimental research may face ethical considerations. Manipulating variables and potentially exposing participants to certain conditions can raise ethical concerns. Researchers must ensure that the benefits of the study outweigh any potential risks or harm to participants.

Correlational Research

Correlational research is a type of non-experimental research that focuses on observing and measuring the relationship between two or more variables. Unlike experimental research, the researcher does not control or manipulate the variables in correlational research. The main purpose of correlational research is to determine if there is a statistical relationship between the variables being studied. It involves comparing two variables and data sources, assessing the relationship between them, and identifying any trends or patterns.

There are several types of correlational studies that can be conducted. One type is positive correlation, which occurs when an increase in one variable is associated with an increase in another variable. For example, there may be a positive correlation between income and education level, meaning that as income increases, education level also tends to increase.

On the other hand, negative correlation refers to a relationship where an increase in one variable is associated with a decrease in another variable. An example of negative correlation could be the relationship between hours spent studying and test scores. As the number of hours spent studying increases, test scores tend to decrease. Lastly, zero correlation indicates that there is no relationship between the variables being studied. This means that changes in one variable do not affect the other variable. For instance, there may be zero correlation between shoe size and intelligence.

Correlational research is commonly used in various fields, including psychology, sociology, and marketing. It provides valuable insights into the relationships between variables and helps researchers understand the patterns and trends in data. However, correlational research has its limitations. Since it does not involve manipulation of variables, it cannot establish causation. It can only identify associations between variables. Additionally, correlational research relies on the accuracy and reliability of the data collected, which can be influenced by various factors.

Causal-Comparative Research

Causal-comparative research is a methodology used to identify cause-effect relationships between independent and dependent variables. It is a type of research method where the researcher tries to find out if there is a causal effect relationship between two or more groups or variables.

The main objective of causal-comparative research is to determine the cause or reason for pre-existing differences in groups of individuals. This research design involves comparing groups that have already been formed based on a specific characteristic or condition. The researcher then analyzes the differences between these groups to identify any causal relationships.

There are two types of causal-comparative research designs: retrospective and prospective. Retrospective causal-comparative research looks at past events or conditions to determine the cause-effect relationship. On the other hand, prospective causal-comparative research looks at current or future events or conditions to identify the causal relationship.

One example of causal-comparative research is a study comparing the critical thinking skills of students who were taught using the inquiry method versus those who were taught using the lecture method. The researcher would compare the two groups of students and analyze the differences in their critical thinking abilities to determine if the teaching method had a causal effect on their skills.

Causal-comparative research has its advantages and disadvantages. One advantage is that it allows researchers to study cause-effect relationships in situations where it is not possible or ethical to manipulate variables. It also provides valuable insights into the factors that contribute to differences between groups.

However, a limitation of causal-comparative research is that it cannot establish a cause-effect relationship with certainty, as there may be other variables or factors that influence the observed differences between groups.

Qualitative Research

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data, qualitative research deals with data types such as text, audio, images, and video, focusing on the variety of human experiences and perspectives.

There are different types of qualitative research methods that researchers can use depending on their study requirements. Some common qualitative research methods include in-depth interviews, focus groups, ethnographic research, content analysis, and case study. In-depth interviews involve conducting one-on-one interviews with participants to gather detailed information about their experiences, opinions, and perspectives. This method allows researchers to delve deep into the thoughts and feelings of individuals and gain a comprehensive understanding of their experiences.

Focus groups involve bringing together a small group of participants to discuss a specific topic or issue. The group dynamic allows for the exploration of different perspectives and the generation of rich and diverse insights. Focus groups are particularly useful for understanding social interactions and group dynamics. Ethnographic research involves immersing the researcher in the natural environment of the participants to observe and understand their behaviors, beliefs, and cultural practices. This method allows for a holistic understanding of the social and cultural context in which individuals operate.

Content analysis involves systematically analyzing textual, audio, or visual data to identify patterns, themes, and meanings. This method is often used to analyze documents, media content, or online discussions to gain insights into societal trends, attitudes, or representations. Case study research involves in-depth investigation of a specific individual, group, or organization. Researchers collect and analyze multiple sources of data to gain a comprehensive understanding of the case under study. Case studies are particularly useful for exploring complex phenomena or unique situations.

Qualitative research provides several advantages. It allows researchers to explore complex and nuanced phenomena in depth, providing rich and detailed insights. It also allows for flexibility and adaptability in the research process, as researchers can adjust their approach based on emerging findings. Additionally, qualitative research is often used to generate hypotheses or theories that can be further tested using quantitative research methods.

However, qualitative research also has some limitations. The findings are often context-specific and may not be generalizable to a larger population. The subjective nature of qualitative data collection and analysis can introduce bias and interpretation challenges. Qualitative research also requires significant time and resources, as data collection and analysis can be time-consuming and labor-intensive.

Quantitative Research

Quantitative research is a type of research that involves collecting and analyzing numerical data to describe characteristics, find correlations, or test hypotheses. It is characterized by structured tools like surveys, substantial sample sizes, closed-ended questions, and reliance on prior studies.

There are two main types of quantitative research: primary and secondary. Primary quantitative research involves collecting data directly from the source, such as through surveys or experiments. Secondary quantitative research, on the other hand, involves analyzing existing data that has been collected by someone else.

Quantitative research methods can be used to quantify opinions, behaviors, attitudes, and other definitive variables related to the market, customers, competitors, and more. It provides a systematic and objective approach to studying phenomena and allows for statistical analysis to draw conclusions.

There are several types of quantitative research designs that can be used, depending on the research objectives . These include descriptive research, correlational research, causal-comparative research, and experimental research as per explained above.

In conclusion, understanding the different types of research is essential for conducting effective and meaningful studies. Each type of research has its own strengths and limitations, and researchers must carefully consider which approach is the most appropriate for their specific research question and objectives. It is important to recognize that research is an iterative process, and different types of research may be used at different stages of a study.

In summary, the various types of research offer different perspectives and methodologies for investigating and understanding the world around us. By utilizing a combination of these approaches, researchers can gain a comprehensive understanding of complex phenomena and make meaningful contributions to their fields of study.

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Different Types of Research Methodologies in Research

Since 2006, oxbridge essays has been the uk’s leading paid essay-writing and dissertation service.

We have helped 10,000s of undergraduate, Masters and PhD students to maximise their grades in essays, dissertations, model-exam answers, applications and other materials. If you would like a free chat about your project with one of our UK staff, then please just reach out on one of the methods below.

A research journey can be compared to navigating unexplored territories. To explore this intellectual terrain successfully, researchers need to employ the appropriate tools: cue research methodologies. Whether you find yourself at the inception of planning your dissertation or are just beginning to contemplate your PhD proposal, the methodology you choose will play a pivotal role in shaping the trajectory of your research journey. In this blog post, we will delve into the three main different types of research methodologies, examining their significance and dissecting the unique features that make each one distinct.

What Does Research Methodology Mean?

Research methodology is the strategic framework that outlines the systematic process researchers use to collect, interpret, and analyse data. It acts as a roadmap, providing a structured path for investigators to follow, ensuring the reliability and validity of their findings. In essence, it is the blueprint that governs your entire research journey.

The Main Types of Research Methodologies

When embarking on a research endeavour, the choice of methodology is crucial. Different types of studies call for different approaches. Let's explore the three main types of research methodologies: Qualitative Research, Quantitative Research, and Mixed Methods.

Qualitative Research : Qualitative research is an exploratory approach focused on gaining a deep understanding of a phenomenon. It employs non-numerical data such as interviews, observations, and open-ended surveys to explore the complexities of human behaviour, attitudes, and experiences. This method is ideal for uncovering nuanced insights that quantitative methods might overlook.

Qualitative research allows for flexibility and adaptability during the research process. It is particularly valuable in fields such as sociology, psychology, and anthropology, where the aim is often to understand the underlying motivations and meanings behind human actions.

Quantitative Research : Quantitative research, on the other hand, concerns the collection and analysis of numerical data. This method employs structured surveys, experiments, and statistical analyses to identify patterns, relationships, and trends within a large dataset. It provides a more objective and measurable approach to research, making it suitable for studies where numerical data is paramount.

Quantitative research is commonly used in fields like economics, medicine, and engineering, where the goal is often to quantify phenomena and draw statistically significant conclusions. This method is characterised by its emphasis on objectivity and the ability to generalise findings to a broader population.

Mixed Methods : Recognising the strengths of both qualitative and quantitative approaches, some researchers opt for a mixed methods methodology. This hybrid approach integrates the best of both worlds, allowing you to gather a comprehensive understanding of your research question. It involves collecting and analysing both qualitative and quantitative data, providing a more holistic perspective.

Mixed methods research is particularly advantageous when a multifaceted understanding of a phenomenon is required. This approach is widely used in education, public health, and social sciences, where combining qualitative depth with quantitative breadth enhances the overall robustness of the study.

How to Choose the Right Methodology for You

Choosing the right research methodology is a multifaceted decision that requires a thoughtful examination of several critical factors. These factors collectively shape the trajectory of your research and contribute significantly to the reliability and validity of your findings.

Research Question At the heart of your decision-making process is the research question. The nature of your inquiry plays a pivotal role in determining the most suitable methodology. For instance, if your goal is to explore the intricate nuances of human experiences, attitudes, or behaviours, qualitative methods such as interviews or observations may be more appropriate. On the other hand, if your research question demands statistical analysis and a quantifiable approach, quantitative methods may be better suited.

Nature of Your Study The characteristics of your study, whether it is exploratory, explanatory, descriptive, or experimental, will also influence your choice of methodology. An exploratory study, aiming to uncover new insights and generate hypotheses, may lean towards qualitative methods. In contrast, an experimental study, seeking to establish cause-and-effect relationships, may require a quantitative approach. Understanding the overarching purpose and design of your study is crucial in aligning the methodology with your research goals.

Available Resources Practical considerations, such as the resources at your disposal, also play a significant role. This encompasses not only financial resources but also the time available, access to participants, and the technological tools required for data collection and analysis. The feasibility of implementing a specific methodology within the constraints of your resources is a key factor in your decision-making process.

Objectives Whether your aim is to explore, describe, explain, or predict, each objective calls for a distinct approach. Your methodology should be tailored to meet these objectives and provide the most effective means of answering your research questions.

Choose Your Research Path Wisely

As you embark on your research voyage, remember that the choice of methodology is a compass that will guide your every step. Whether you opt for the depth of qualitative research, the precision of quantitative methods, or the comprehensive approach of mixed methods, understanding the intricacies of each is crucial for success.

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Example of research methodology

Research Methodology is a way of elucidating how a researcher is going to carry out their research. It is actually a logical & systematic strategy to resolve a research problem. Your research methodology must simply justify the practical statement “how” of your research topic. Choosing a simple and effective research methodology can be the toughest task. So, for this reason, HIGS will help you to choose your effective research methodology.

• A research framework including philosophies, statement, hypothesis, methods, procedures, and methods used to augment the consistency and validity of the research and philosophical orientation of the research.
• PhD research methodology is the justification for choosing PhD research methodology and it reveals the consideration and limitations of the research methodology.

We have given a brief details about the following topics

• Concept research methodology

Research methodology notes for PhD students

Research methodology syllabus for phd.

• Research methodology MCQ for PhD entrance exam

Get research methodology notes for PhD entrance. And download the research methodology question paper for PhD entrance pdf. Our team has the latest pre PhD research methodology MCQ for PhD. And we will explain the research methodology syllabus for PhD entrance exam. You can talk with our experts and get to know about the best book for research methodology for PhD entrance, and research methodology PhD coursework notes. We will give you the latest updates on the research methodology syllabus for the entrance exam 2024. It may differ based on the types of PhD research and methodology. Here, we offer solved MCQ on research methodology pdf. You can reach HIGS and we provide the following,

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Our team will guide you in how to prepare for the PhD entrance exam and give you guidelines for the research aptitude test for PhD entrance pdf. You can also download your PhD question paper, research methodology syllabus at anna university, research methodology question paper for PhD course work pdf, multiple choice questions on research report writing pdf, data science, methodology final exam answers, and more. You can download social science research problems MCQ, and all the research domains.

Example of research methodology extra content

You can check out the research methodology for PhD entrance exams. You can download the research methodology for PhD entrance PDF from here. You will get a sample of the research methodology from experts. Our expert team at HIGS will give you the best research methodology topics, and syllabus of research methodology for PhD, PhD interview questions on research methodology, and more.

What is research in PhD?

It aims to get advanced knowledge & benefits by developing scientific theories, concepts, and ideas. Your research may include various PhD research methodology types, proposals, papers, and a thesis. You can download the research methodology objective questions pdf here.

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• Introduction
• Aim of the study
• Scope and period
• Method of study
• Data processing
• Limitation of the research study

In a large country like India, it is usual to have a great and huge system of higher education with a great number of universities and colleges. The number of PhD students looking for University registration for higher education has increased manifold and will continue to increase. So in your PhD research methodology should contain the following steps.

• Concept of the research methodology, Objectives and purpose of the research and the types of the research
• Qualities of Researcher
• Importance of the research
• Process of research
• Problem of research
• Features, methods, importance, characteristics, concepts, and types of research design
• Research case study
• Hypothesis and it’s testing
• Sample survey and sampling procedure.

Concept of research and research Methodology

Research is defined as the search for acquaintance under the specific topics or specific zone. It is a scientific and methodical look for gathering data for a particular topic or problem. It is also recognized as the art of scientific examination or study. There are numerous social scientists have explained the terms of research in various ways.

Research methodology is a specific procedure or technique used to recognize, choose, progress, and investigate information about a topic. The methodology part of the research paper should give a clear detail about the validity and reliability of the research for the readers.

Types of research methodology

Usually, research methods can be broadly classified into two categories. They are applied research methodology and fundamental research methods.

Applied research methodology

In this method, new methods and hypotheses are incorporated into the existing methods and hypothesis. The problems will be identified from the point of one discipline.

Fundamental research methodology

This methodology is aims to resolve problems by the addition of the application of discipline. In this methodology, several disciplines are work together for resolving the specific issue.

• Conclusive research methodology

Conclusive studies, on the contrary, intend to offer last and final answers to research questions. This type of methodology is well structured and designed systematically. And it is an official and perfect methodology and needs to be followed under specific testing.

• Exploratory research methodology

The exploratory research method is having the main aim of exploring the research area and in this methodology; there won’t be any attempt to present final and conclusive solutions to research questions. And also flexible investigations are given in this research methodology. This methodology won’t have information apart from the research topic and this will not involve in the testing of hypotheses.

Types of research methodology based on research design

On the basis of research design and the structure of research, the types of research methods can be categorized into 2 criteria and they are,

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Don’t know how to write research methodology, have a deep conversation with our team of experts…, mcq on research methodology for phd entrance.

A definite stage of workability at a certain level is known as aptitude. For University registration you must score on your entrance exams, for this all the PhD entrance exams mostly give you multiple choices of questions. Hereby, we offer you with the MCQ for law, MCQ for Microbiology, MCQ on report writing in research methodology, research aptitude MCQ, MCQ on the research process, MCQ for Engineering and technological PhD research, solved MCQ for research methodology and more.

Accept it or not, MCQ for PhD entrance exams are now universally accepted and adapted format for all the Students whoever attempting for entrance exams and with the intention of testing their IQ and knowledge in relevant to your research topics and domain. Students find this MCQ in entrance exams as confusing, difficult, and risky. Some experience that the questions are intentionally phrased and categorized and the students choose the wrong answer. Despite the fact that attending the MCQ's during the entrance exams of your PhD, students must be relaxed and attempt the test without getting nervous. Here we have given some tips to be followed while attempting the Multiple Choice Questions in your PhD entrance exams.

• Understand the questions carefully.
• Try to guess what the answer is before you go for the given choices.
• If you are not sure about your answer, eliminate the unnecessary answers and try to keep in mind if any of the answers left are related to those questions or a subject. Try to recollect the word which is given in the choices and if you have never heard of a choice in your subject it is preferred to be eliminated then it is probably not the answer.
• After eliminating all other unwanted choices and have a logical guess associated with the question. Remember, the first guess is generally more reliable unless you get a major revelation along the way.
• If you are still confused, mark the question in which you are confused so you can get it easier later and go on with the exam. Sometimes the answer you're looking for may be specified for a different question. And you can set off that question later.
• Never neglect the multiple-choice question blank. You have a 20-25% chance of predicting it correctly by guessing.
• If your options are available with all of the above choice, in that situation, If 2 or more of the answers are correct, then the all-of-the-above option is the correct answer.
• Sometimes if there are 2 options that are similar except for one word. Such a pair shows that the question is focused there. Usually you can assume the answer is one of that pair.

Research methodology question bank with answers pdf

Research methodology syllabus for PhD entrance exams includes qualities of a researcher, components of a research problem, types of research, research design, case study research, merits and demerits of the research, statistical applications of the research, research ethics, logic and reasoning, structure and components of a research report, types of the research report, characteristics of a good research report, and more.

Best research methodology books for PhD

Books are your best guide. There are some great books are available written and edited by great scientists and authors. And you can refer the whole book under www.educatorstechnology.com

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Frequently asked questions, what is research methodology, how do you write a research method in phd thesis and synopsis.

• Give details about your methodological approach.
• Explain your methods of data collection.
• Illustrate your methods of analysis.

What are research methodology and research methods?

What are the major types of research methods, what are quantitative and qualitative research methods, what are the 3 research methods, what are examples of research methods, discuss about the importance illustrations, graphs, photographs in research paper, explain bibliography, explain about the different steps involved in formulating a research plan, give an account on the copyright issues and plagiarism, what is multi-stage sampling, what is the importance of research funding, explain deliberate sampling, what you meant by stratified sampling, what does sampling cases mean, what are the core properties of dissertation, give one example about scientific knowledge, nine years of old children are taller than 7 years old ones- state which method of study it belongs to, what is deductive theory, which technique is generally when the population is finite, how should be the good hypothesis, how should be the research, how should be the data of the research, how to improve the validity of the research, which is a non-probability sample, how to write a research report.

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Home » Scientific Research – Types, Purpose and Guide

Scientific Research – Types, Purpose and Guide

Table of Contents

Scientific Research

Definition:

Scientific research is the systematic and empirical investigation of phenomena, theories, or hypotheses, using various methods and techniques in order to acquire new knowledge or to validate existing knowledge.

It involves the collection, analysis, interpretation, and presentation of data, as well as the formulation and testing of hypotheses. Scientific research can be conducted in various fields, such as natural sciences, social sciences, and engineering, and may involve experiments, observations, surveys, or other forms of data collection. The goal of scientific research is to advance knowledge, improve understanding, and contribute to the development of solutions to practical problems.

Types of Scientific Research

There are different types of scientific research, which can be classified based on their purpose, method, and application. In this response, we will discuss the four main types of scientific research.

Descriptive Research

Descriptive research aims to describe or document a particular phenomenon or situation, without altering it in any way. This type of research is usually done through observation, surveys, or case studies. Descriptive research is useful in generating ideas, understanding complex phenomena, and providing a foundation for future research. However, it does not provide explanations or causal relationships between variables.

Exploratory Research

Exploratory research aims to explore a new area of inquiry or develop initial ideas for future research. This type of research is usually conducted through observation, interviews, or focus groups. Exploratory research is useful in generating hypotheses, identifying research questions, and determining the feasibility of a larger study. However, it does not provide conclusive evidence or establish cause-and-effect relationships.

Experimental Research

Experimental research aims to test cause-and-effect relationships between variables by manipulating one variable and observing the effects on another variable. This type of research involves the use of an experimental group, which receives a treatment, and a control group, which does not receive the treatment. Experimental research is useful in establishing causal relationships, replicating results, and controlling extraneous variables. However, it may not be feasible or ethical to manipulate certain variables in some contexts.

Correlational Research

Correlational research aims to examine the relationship between two or more variables without manipulating them. This type of research involves the use of statistical techniques to determine the strength and direction of the relationship between variables. Correlational research is useful in identifying patterns, predicting outcomes, and testing theories. However, it does not establish causation or control for confounding variables.

Scientific Research Methods

Scientific research methods are used in scientific research to investigate phenomena, acquire knowledge, and answer questions using empirical evidence. Here are some commonly used scientific research methods:

Observational Studies

This method involves observing and recording phenomena as they occur in their natural setting. It can be done through direct observation or by using tools such as cameras, microscopes, or sensors.

Experimental Studies

This method involves manipulating one or more variables to determine the effect on the outcome. This type of study is often used to establish cause-and-effect relationships.

Survey Research

This method involves collecting data from a large number of people by asking them a set of standardized questions. Surveys can be conducted in person, over the phone, or online.

Case Studies

This method involves in-depth analysis of a single individual, group, or organization. Case studies are often used to gain insights into complex or unusual phenomena.

Meta-analysis

This method involves combining data from multiple studies to arrive at a more reliable conclusion. This technique can be used to identify patterns and trends across a large number of studies.

Qualitative Research

This method involves collecting and analyzing non-numerical data, such as interviews, focus groups, or observations. This type of research is often used to explore complex phenomena and to gain an understanding of people’s experiences and perspectives.

Quantitative Research

This method involves collecting and analyzing numerical data using statistical techniques. This type of research is often used to test hypotheses and to establish cause-and-effect relationships.

Longitudinal Studies

This method involves following a group of individuals over a period of time to observe changes and to identify patterns and trends. This type of study can be used to investigate the long-term effects of a particular intervention or exposure.

Data Analysis Methods

There are many different data analysis methods used in scientific research, and the choice of method depends on the type of data being collected and the research question. Here are some commonly used data analysis methods:

• Descriptive statistics: This involves using summary statistics such as mean, median, mode, standard deviation, and range to describe the basic features of the data.
• Inferential statistics: This involves using statistical tests to make inferences about a population based on a sample of data. Examples of inferential statistics include t-tests, ANOVA, and regression analysis.
• Qualitative analysis: This involves analyzing non-numerical data such as interviews, focus groups, and observations. Qualitative analysis may involve identifying themes, patterns, or categories in the data.
• Content analysis: This involves analyzing the content of written or visual materials such as articles, speeches, or images. Content analysis may involve identifying themes, patterns, or categories in the content.
• Data mining: This involves using automated methods to analyze large datasets to identify patterns, trends, or relationships in the data.
• Machine learning: This involves using algorithms to analyze data and make predictions or classifications based on the patterns identified in the data.

Application of Scientific Research

Scientific research has numerous applications in many fields, including:

• Medicine and healthcare: Scientific research is used to develop new drugs, medical treatments, and vaccines. It is also used to understand the causes and risk factors of diseases, as well as to develop new diagnostic tools and medical devices.
• Agriculture : Scientific research is used to develop new crop varieties, to improve crop yields, and to develop more sustainable farming practices.
• Technology and engineering : Scientific research is used to develop new technologies and engineering solutions, such as renewable energy systems, new materials, and advanced manufacturing techniques.
• Environmental science : Scientific research is used to understand the impacts of human activity on the environment and to develop solutions for mitigating those impacts. It is also used to monitor and manage natural resources, such as water and air quality.
• Education : Scientific research is used to develop new teaching methods and educational materials, as well as to understand how people learn and develop.
• Business and economics: Scientific research is used to understand consumer behavior, to develop new products and services, and to analyze economic trends and policies.
• Social sciences : Scientific research is used to understand human behavior, attitudes, and social dynamics. It is also used to develop interventions to improve social welfare and to inform public policy.

How to Conduct Scientific Research

Conducting scientific research involves several steps, including:

• Identify a research question: Start by identifying a question or problem that you want to investigate. This question should be clear, specific, and relevant to your field of study.
• Conduct a literature review: Before starting your research, conduct a thorough review of existing research in your field. This will help you identify gaps in knowledge and develop hypotheses or research questions.
• Develop a research plan: Once you have a research question, develop a plan for how you will collect and analyze data to answer that question. This plan should include a detailed methodology, a timeline, and a budget.
• Collect data: Depending on your research question and methodology, you may collect data through surveys, experiments, observations, or other methods.
• Analyze data: Once you have collected your data, analyze it using appropriate statistical or qualitative methods. This will help you draw conclusions about your research question.
• Interpret results: Based on your analysis, interpret your results and draw conclusions about your research question. Discuss any limitations or implications of your findings.
• Communicate results: Finally, communicate your findings to others in your field through presentations, publications, or other means.

Purpose of Scientific Research

The purpose of scientific research is to systematically investigate phenomena, acquire new knowledge, and advance our understanding of the world around us. Scientific research has several key goals, including:

• Exploring the unknown: Scientific research is often driven by curiosity and the desire to explore uncharted territory. Scientists investigate phenomena that are not well understood, in order to discover new insights and develop new theories.
• Testing hypotheses: Scientific research involves developing hypotheses or research questions, and then testing them through observation and experimentation. This allows scientists to evaluate the validity of their ideas and refine their understanding of the phenomena they are studying.
• Solving problems: Scientific research is often motivated by the desire to solve practical problems or address real-world challenges. For example, researchers may investigate the causes of a disease in order to develop new treatments, or explore ways to make renewable energy more affordable and accessible.
• Advancing knowledge: Scientific research is a collective effort to advance our understanding of the world around us. By building on existing knowledge and developing new insights, scientists contribute to a growing body of knowledge that can be used to inform decision-making, solve problems, and improve our lives.

Examples of Scientific Research

Here are some examples of scientific research that are currently ongoing or have recently been completed:

• Clinical trials for new treatments: Scientific research in the medical field often involves clinical trials to test new treatments for diseases and conditions. For example, clinical trials may be conducted to evaluate the safety and efficacy of new drugs or medical devices.
• Genomics research: Scientists are conducting research to better understand the human genome and its role in health and disease. This includes research on genetic mutations that can cause diseases such as cancer, as well as the development of personalized medicine based on an individual’s genetic makeup.
• Climate change: Scientific research is being conducted to understand the causes and impacts of climate change, as well as to develop solutions for mitigating its effects. This includes research on renewable energy technologies, carbon capture and storage, and sustainable land use practices.
• Neuroscience : Scientists are conducting research to understand the workings of the brain and the nervous system, with the goal of developing new treatments for neurological disorders such as Alzheimer’s disease and Parkinson’s disease.
• Artificial intelligence: Researchers are working to develop new algorithms and technologies to improve the capabilities of artificial intelligence systems. This includes research on machine learning, computer vision, and natural language processing.
• Space exploration: Scientific research is being conducted to explore the cosmos and learn more about the origins of the universe. This includes research on exoplanets, black holes, and the search for extraterrestrial life.

When to use Scientific Research

Some specific situations where scientific research may be particularly useful include:

• Solving problems: Scientific research can be used to investigate practical problems or address real-world challenges. For example, scientists may investigate the causes of a disease in order to develop new treatments, or explore ways to make renewable energy more affordable and accessible.
• Decision-making: Scientific research can provide evidence-based information to inform decision-making. For example, policymakers may use scientific research to evaluate the effectiveness of different policy options or to make decisions about public health and safety.
• Innovation : Scientific research can be used to develop new technologies, products, and processes. For example, research on materials science can lead to the development of new materials with unique properties that can be used in a range of applications.
• Knowledge creation : Scientific research is an important way of generating new knowledge and advancing our understanding of the world around us. This can lead to new theories, insights, and discoveries that can benefit society.

Advantages of Scientific Research

There are many advantages of scientific research, including:

• Improved understanding : Scientific research allows us to gain a deeper understanding of the world around us, from the smallest subatomic particles to the largest celestial bodies.
• Evidence-based decision making: Scientific research provides evidence-based information that can inform decision-making in many fields, from public policy to medicine.
• Technological advancements: Scientific research drives technological advancements in fields such as medicine, engineering, and materials science. These advancements can improve quality of life, increase efficiency, and reduce costs.
• New discoveries: Scientific research can lead to new discoveries and breakthroughs that can advance our knowledge in many fields. These discoveries can lead to new theories, technologies, and products.
• Economic benefits : Scientific research can stimulate economic growth by creating new industries and jobs, and by generating new technologies and products.
• Improved health outcomes: Scientific research can lead to the development of new medical treatments and technologies that can improve health outcomes and quality of life for people around the world.
• Increased innovation: Scientific research encourages innovation by promoting collaboration, creativity, and curiosity. This can lead to new and unexpected discoveries that can benefit society.

Limitations of Scientific Research

Scientific research has some limitations that researchers should be aware of. These limitations can include:

• Research design limitations : The design of a research study can impact the reliability and validity of the results. Poorly designed studies can lead to inaccurate or inconclusive results. Researchers must carefully consider the study design to ensure that it is appropriate for the research question and the population being studied.
• Sample size limitations: The size of the sample being studied can impact the generalizability of the results. Small sample sizes may not be representative of the larger population, and may lead to incorrect conclusions.
• Time and resource limitations: Scientific research can be costly and time-consuming. Researchers may not have the resources necessary to conduct a large-scale study, or may not have sufficient time to complete a study with appropriate controls and analysis.
• Ethical limitations : Certain types of research may raise ethical concerns, such as studies involving human or animal subjects. Ethical concerns may limit the scope of the research that can be conducted, or require additional protocols and procedures to ensure the safety and well-being of participants.
• Limitations of technology: Technology may limit the types of research that can be conducted, or the accuracy of the data collected. For example, certain types of research may require advanced technology that is not yet available, or may be limited by the accuracy of current measurement tools.
• Limitations of existing knowledge: Existing knowledge may limit the types of research that can be conducted. For example, if there is limited knowledge in a particular field, it may be difficult to design a study that can provide meaningful results.

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Modernizing the Data Infrastructure for Clinical Research to Meet Evolving Demands for Evidence

• 1 Verily Life Sciences, South San Francisco, California
• 2 Center for Biostatistics & Qualitative Methodology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
• 3 Bakar Computational Health Sciences Institute, University of California, San Francisco
• 4 Center for Data-Driven Insights and Innovation, University of California Health, Oakland
• 5 Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
• 6 Departments of Surgery and Radiology and Institute for Health Policy Studies, University of California, San Francisco
• 7 Anesthesiology and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia
• 8 Biogen, Boston, Massachusetts
• 9 Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
• 10 Yale University School of Medicine, New Haven, Connecticut
• 11 National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research Programme, London, United Kingdom
• 12 Intensive Care National Audit & Research Centre (ICNARC), London, United Kingdom
• 13 Highlander Health, Dallas, Texas

Importance   The ways in which we access, acquire, and use data in clinical trials have evolved very little over time, resulting in a fragmented and inefficient system that limits the amount and quality of evidence that can be generated.

Observations   Clinical trial design has advanced steadily over several decades. Yet the infrastructure for clinical trial data collection remains expensive and labor intensive and limits the amount of evidence that can be collected to inform whether and how interventions work for different patient populations. Meanwhile, there is increasing demand for evidence from randomized clinical trials to inform regulatory decisions, payment decisions, and clinical care. Although substantial public and industry investment in advancing electronic health record interoperability, data standardization, and the technology systems used for data capture have resulted in significant progress on various aspects of data generation, there is now a need to combine the results of these efforts and apply them more directly to the clinical trial data infrastructure.

Conclusions and Relevance   We describe a vision for a modernized infrastructure that is centered around 2 related concepts. First, allowing the collection and rigorous evaluation of multiple data sources and types and, second, enabling the possibility to reuse health data for multiple purposes. We address the need for multidisciplinary collaboration and suggest ways to measure progress toward this goal.

Read More About

Franklin JB , Marra C , Abebe KZ, et al. Modernizing the Data Infrastructure for Clinical Research to Meet Evolving Demands for Evidence. JAMA. Published online August 05, 2024. doi:10.1001/jama.2024.0268

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