identifying variables in an experiment

What Is a Variable in Science?

Understanding Variables in a Science Experiment

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Variables are an important part of science projects and experiments. What is a variable? Basically, a variable is any factor that can be controlled, changed, or measured in an experiment. Scientific experiments have several types of variables. The independent and dependent variables are the ones usually plotted on a chart or graph, but there are other types of variables you may encounter.

Types of Variables

• Independent Variable: The independent variable is the one condition that you change in an experiment. Example: In an experiment measuring the effect of temperature on solubility, the independent variable is temperature.
• Dependent Variable: The dependent variable is the variable that you measure or observe. The dependent variable gets its name because it is the factor that is dependent on the state of the independent variable . Example: In the experiment measuring the effect of temperature on solubility, solubility would be the dependent variable.
• Controlled Variable: A controlled variable or constant variable is a variable that does not change during an experiment. Example : In the experiment measuring the effect of temperature on solubility, controlled variable could include the source of water used in the experiment, the size and type of containers used to mix chemicals, and the amount of mixing time allowed for each solution.
• Extraneous Variables: Extraneous variables are "extra" variables that may influence the outcome of an experiment but aren't taken into account during measurement. Ideally, these variables won't impact the final conclusion drawn by the experiment, but they may introduce error into scientific results. If you are aware of any extraneous variables, you should enter them in your lab notebook . Examples of extraneous variables include accidents, factors you either can't control or can't measure, and factors you consider unimportant. Every experiment has extraneous variables. Example : You are conducting an experiment to see which paper airplane design flies longest. You may consider the color of the paper to be an extraneous variable. You note in your lab book that different colors of papers were used. Ideally, this variable does not affect your outcome.

Using Variables in Science Experiment

In a science experiment , only one variable is changed at a time (the independent variable) to test how this changes the dependent variable. The researcher may measure other factors that either remain constant or change during the course of the experiment but are not believed to affect its outcome. These are controlled variables. Any other factors that might be changed if someone else conducted the experiment but seemed unimportant should also be noted. Also, any accidents that occur should be recorded. These are extraneous variables.

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• Guide to Experimental Design | Overview, Steps, & Examples

Guide to Experimental Design | Overview, 5 steps & Examples

Published on December 3, 2019 by Rebecca Bevans . Revised on June 21, 2023.

Experiments are used to study causal relationships . You manipulate one or more independent variables and measure their effect on one or more dependent variables.

Experimental design create a set of procedures to systematically test a hypothesis . A good experimental design requires a strong understanding of the system you are studying.

There are five key steps in designing an experiment:

• Consider your variables and how they are related
• Write a specific, testable hypothesis
• Design experimental treatments to manipulate your independent variable
• Assign subjects to groups, either between-subjects or within-subjects
• Plan how you will measure your dependent variable

For valid conclusions, you also need to select a representative sample and control any  extraneous variables that might influence your results. If random assignment of participants to control and treatment groups is impossible, unethical, or highly difficult, consider an observational study instead. This minimizes several types of research bias, particularly sampling bias , survivorship bias , and attrition bias as time passes.

Table of contents

Step 1: define your variables, step 2: write your hypothesis, step 3: design your experimental treatments, step 4: assign your subjects to treatment groups, step 5: measure your dependent variable, other interesting articles, frequently asked questions about experiments.

You should begin with a specific research question . We will work with two research question examples, one from health sciences and one from ecology:

To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.

Start by simply listing the independent and dependent variables .

Then you need to think about possible extraneous and confounding variables and consider how you might control  them in your experiment.

Finally, you can put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.

Here we predict that increasing temperature will increase soil respiration and decrease soil moisture, while decreasing soil moisture will lead to decreased soil respiration.

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Now that you have a strong conceptual understanding of the system you are studying, you should be able to write a specific, testable hypothesis that addresses your research question.

The next steps will describe how to design a controlled experiment . In a controlled experiment, you must be able to:

• Systematically and precisely manipulate the independent variable(s).
• Precisely measure the dependent variable(s).
• Control any potential confounding variables.

If your study system doesn’t match these criteria, there are other types of research you can use to answer your research question.

How you manipulate the independent variable can affect the experiment’s external validity – that is, the extent to which the results can be generalized and applied to the broader world.

First, you may need to decide how widely to vary your independent variable.

• just slightly above the natural range for your study region.
• over a wider range of temperatures to mimic future warming.
• over an extreme range that is beyond any possible natural variation.

Second, you may need to choose how finely to vary your independent variable. Sometimes this choice is made for you by your experimental system, but often you will need to decide, and this will affect how much you can infer from your results.

• a categorical variable : either as binary (yes/no) or as levels of a factor (no phone use, low phone use, high phone use).
• a continuous variable (minutes of phone use measured every night).

How you apply your experimental treatments to your test subjects is crucial for obtaining valid and reliable results.

First, you need to consider the study size : how many individuals will be included in the experiment? In general, the more subjects you include, the greater your experiment’s statistical power , which determines how much confidence you can have in your results.

Then you need to randomly assign your subjects to treatment groups . Each group receives a different level of the treatment (e.g. no phone use, low phone use, high phone use).

You should also include a control group , which receives no treatment. The control group tells us what would have happened to your test subjects without any experimental intervention.

When assigning your subjects to groups, there are two main choices you need to make:

• A completely randomized design vs a randomized block design .
• A between-subjects design vs a within-subjects design .

Randomization

An experiment can be completely randomized or randomized within blocks (aka strata):

• In a completely randomized design , every subject is assigned to a treatment group at random.
• In a randomized block design (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

Sometimes randomization isn’t practical or ethical , so researchers create partially-random or even non-random designs. An experimental design where treatments aren’t randomly assigned is called a quasi-experimental design .

Between-subjects vs. within-subjects

In a between-subjects design (also known as an independent measures design or classic ANOVA design), individuals receive only one of the possible levels of an experimental treatment.

In medical or social research, you might also use matched pairs within your between-subjects design to make sure that each treatment group contains the same variety of test subjects in the same proportions.

In a within-subjects design (also known as a repeated measures design), every individual receives each of the experimental treatments consecutively, and their responses to each treatment are measured.

Within-subjects or repeated measures can also refer to an experimental design where an effect emerges over time, and individual responses are measured over time in order to measure this effect as it emerges.

Counterbalancing (randomizing or reversing the order of treatments among subjects) is often used in within-subjects designs to ensure that the order of treatment application doesn’t influence the results of the experiment.

Finally, you need to decide how you’ll collect data on your dependent variable outcomes. You should aim for reliable and valid measurements that minimize research bias or error.

Some variables, like temperature, can be objectively measured with scientific instruments. Others may need to be operationalized to turn them into measurable observations.

• Ask participants to record what time they go to sleep and get up each day.
• Ask participants to wear a sleep tracker.

How precisely you measure your dependent variable also affects the kinds of statistical analysis you can use on your data.

Experiments are always context-dependent, and a good experimental design will take into account all of the unique considerations of your study system to produce information that is both valid and relevant to your research question.

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

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Likert scale

Research bias

• Implicit bias
• Framing effect
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

• A testable hypothesis
• At least one independent variable that can be precisely manipulated
• At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

• How you will manipulate the variable(s)
• How you will control for any potential confounding variables
• How many subjects or samples will be included in the study
• How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

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Independent and Dependent Variables

Saul McLeod, PhD

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On This Page:

In research, a variable is any characteristic, number, or quantity that can be measured or counted in experimental investigations . One is called the dependent variable, and the other is the independent variable.

In research, the independent variable is manipulated to observe its effect, while the dependent variable is the measured outcome. Essentially, the independent variable is the presumed cause, and the dependent variable is the observed effect.

Variables provide the foundation for examining relationships, drawing conclusions, and making predictions in research studies.

Independent Variable

In psychology, the independent variable is the variable the experimenter manipulates or changes and is assumed to directly affect the dependent variable.

It’s considered the cause or factor that drives change, allowing psychologists to observe how it influences behavior, emotions, or other dependent variables in an experimental setting. Essentially, it’s the presumed cause in cause-and-effect relationships being studied.

For example, allocating participants to drug or placebo conditions (independent variable) to measure any changes in the intensity of their anxiety (dependent variable).

In a well-designed experimental study , the independent variable is the only important difference between the experimental (e.g., treatment) and control (e.g., placebo) groups.

By changing the independent variable and holding other factors constant, psychologists aim to determine if it causes a change in another variable, called the dependent variable.

For example, in a study investigating the effects of sleep on memory, the amount of sleep (e.g., 4 hours, 8 hours, 12 hours) would be the independent variable, as the researcher might manipulate or categorize it to see its impact on memory recall, which would be the dependent variable.

Dependent Variable

In psychology, the dependent variable is the variable being tested and measured in an experiment and is “dependent” on the independent variable.

In psychology, a dependent variable represents the outcome or results and can change based on the manipulations of the independent variable. Essentially, it’s the presumed effect in a cause-and-effect relationship being studied.

An example of a dependent variable is depression symptoms, which depend on the independent variable (type of therapy).

In an experiment, the researcher looks for the possible effect on the dependent variable that might be caused by changing the independent variable.

For instance, in a study examining the effects of a new study technique on exam performance, the technique would be the independent variable (as it is being introduced or manipulated), while the exam scores would be the dependent variable (as they represent the outcome of interest that’s being measured).

Examples in Research Studies

For example, we might change the type of information (e.g., organized or random) given to participants to see how this might affect the amount of information remembered.

In this example, the type of information is the independent variable (because it changes), and the amount of information remembered is the dependent variable (because this is being measured).

For the following hypotheses, name the IV and the DV.

1. Lack of sleep significantly affects learning in 10-year-old boys.

IV……………………………………………………

DV…………………………………………………..

2. Social class has a significant effect on IQ scores.

DV……………………………………………….…

3. Stressful experiences significantly increase the likelihood of headaches.

4. Time of day has a significant effect on alertness.

Operationalizing Variables

To ensure cause and effect are established, it is important that we identify exactly how the independent and dependent variables will be measured; this is known as operationalizing the variables.

Operational variables (or operationalizing definitions) refer to how you will define and measure a specific variable as it is used in your study. This enables another psychologist to replicate your research and is essential in establishing reliability (achieving consistency in the results).

For example, if we are concerned with the effect of media violence on aggression, then we need to be very clear about what we mean by the different terms. In this case, we must state what we mean by the terms “media violence” and “aggression” as we will study them.

Therefore, you could state that “media violence” is operationally defined (in your experiment) as ‘exposure to a 15-minute film showing scenes of physical assault’; “aggression” is operationally defined as ‘levels of electrical shocks administered to a second ‘participant’ in another room.

In another example, the hypothesis “Young participants will have significantly better memories than older participants” is not operationalized. How do we define “young,” “old,” or “memory”? “Participants aged between 16 – 30 will recall significantly more nouns from a list of twenty than participants aged between 55 – 70” is operationalized.

The key point here is that we have clarified what we mean by the terms as they were studied and measured in our experiment.

If we didn’t do this, it would be very difficult (if not impossible) to compare the findings of different studies to the same behavior.

Operationalization has the advantage of generally providing a clear and objective definition of even complex variables. It also makes it easier for other researchers to replicate a study and check for reliability .

For the following hypotheses, name the IV and the DV and operationalize both variables.

1. Women are more attracted to men without earrings than men with earrings.

I.V._____________________________________________________________

D.V. ____________________________________________________________

Operational definitions:

I.V. ____________________________________________________________

2. People learn more when they study in a quiet versus noisy place.

I.V. _________________________________________________________

D.V. ___________________________________________________________

3. People who exercise regularly sleep better at night.

Can there be more than one independent or dependent variable in a study?

Yes, it is possible to have more than one independent or dependent variable in a study.

In some studies, researchers may want to explore how multiple factors affect the outcome, so they include more than one independent variable.

Similarly, they may measure multiple things to see how they are influenced, resulting in multiple dependent variables. This allows for a more comprehensive understanding of the topic being studied.

What are some ethical considerations related to independent and dependent variables?

Ethical considerations related to independent and dependent variables involve treating participants fairly and protecting their rights.

Researchers must ensure that participants provide informed consent and that their privacy and confidentiality are respected. Additionally, it is important to avoid manipulating independent variables in ways that could cause harm or discomfort to participants.

Researchers should also consider the potential impact of their study on vulnerable populations and ensure that their methods are unbiased and free from discrimination.

Ethical guidelines help ensure that research is conducted responsibly and with respect for the well-being of the participants involved.

Can qualitative data have independent and dependent variables?

Yes, both quantitative and qualitative data can have independent and dependent variables.

In quantitative research, independent variables are usually measured numerically and manipulated to understand their impact on the dependent variable. In qualitative research, independent variables can be qualitative in nature, such as individual experiences, cultural factors, or social contexts, influencing the phenomenon of interest.

The dependent variable, in both cases, is what is being observed or studied to see how it changes in response to the independent variable.

So, regardless of the type of data, researchers analyze the relationship between independent and dependent variables to gain insights into their research questions.

Can the same variable be independent in one study and dependent in another?

Yes, the same variable can be independent in one study and dependent in another.

The classification of a variable as independent or dependent depends on how it is used within a specific study. In one study, a variable might be manipulated or controlled to see its effect on another variable, making it independent.

However, in a different study, that same variable might be the one being measured or observed to understand its relationship with another variable, making it dependent.

The role of a variable as independent or dependent can vary depending on the research question and study design.

Identifying Independent and Dependent Variables

Hey guys! Welcome to this Mometrix video over Independent and Dependent Variables .

There are two primary variables in a scientific experiment: the independent and dependent variable.

What is an independent variable?

The independent variable is the variable that is controlled throughout the experiment, but it is not affected by any other variable. So, like its name suggests, it is independent from other variables. Time, for example, will always be an independent variable. Let’s say you wanted to test how tall a tree would grow after eight months of treating it with a certain type of fertilizer. The height of the tree may change, and you can change the amount of fertilizer, but that will have no effect on the eight month period. You can never speed up time or slow time down. It will always be independent from anything we can do. However, you can change the amount of time you are measuring something.

What is a dependent variable?

The dependent variable is the variable being tested. The dependent variable depends on other factors. In our last example we said, “how tall will a tree grow after eight months of treating it with a certain type of fertilizer?” Well, the height of the tree is our dependent variable. It is dependent on the amount of time, the type of fertilizer, as well as other things like the region it’s growing in, temperature, and so on.

It may be helpful to think of the independent variable and dependent variable in the same vein as cause and effect. If the independent variable is changed, then an effect will be observed in the dependent variable.

Both independent and dependent variables may change during the duration of the experiment. However, the experimenter is in control of changing the independent variable but not the dependent variable. The dependent variable solely changes under the influence of the independent variable.

When graphing it is sort of a consensus that you would always use the x -axis to plot the independent variable and the y -axis to plot the dependent variable. However, some people don’t, and that is why it is so important to label your axes!

I hope that this video was helpful! If you enjoyed it, then be sure to give us a thumbs up, and subscribe to our channel for further videos.

See ya guys next time!

Independent and Dependent Variable Practice Questions

  Carlos is developing a new chocolate chip recipe. While testing recipes out, he notices that when he adds less and less flour to the cookie dough, the cookies get wider and spread out on the pan. What is the dependent variable in Carlos’ experiment?

Type of flour used

Amount of chocolate chips added

Amount of flour added

Size of baked cookies

Remember that the dependent variable depends on the independent variable. In this problem, we see that the width (a.k.a. the “size”) of each cookie depends on how much flour Carlos puts in the dough.

*Another helpful rule to memorize is: the dependent variable is what we observe (or measure) happening in an experiment. But, as for the independent variable, it is usually what we change in an experiment. In this problem, the independent variable is the amount of flour that Carlos adds to the dough.

Time (weeks passed)

Length of worms in the compost bin

Amount of worms in the compost bin

Amount of compost generated

The correct answer is A. While we may not be making time go on or changing time itself, we see that the amount of worms grows as time goes on. Hence: the worm population depends on how much time has passed.

*Also, even if we didn’t fully understand what was going on in this experiment, we can count on two “cheat cards:” time is almost always an independent variable; and we usually put the independent variable on the x -axis and the dependent variable on the y -axis when graphing experiment results.

  You’ve been given the equation \(q=7.4p^2+9\) and the table:

Using this information, we can deduce that the dependent variable is most likely _____.

The correct answer is C. If we were only given the equation \(q=7.4p^2+9\), we couldn’t decide which variable depends on the other (because we could easily re-write the equation as \(p=\sqrt{\frac{q-9}{7.4}}\)). However, because we know that p is the input -value and q is the output -value, we also know that q depends on p . (What we pull out depends on what we put into the equation.) Also, since we’ve already been given pre-set values of p , it’s safe to assume that p is the independent variable; because the value of p will not be impacted by a change in q .

What is the independent variable in Briana’s experiment?

Amount of mold growth (inches 2 )

Area of bread slices (inches 2 )

The correct answer is B. While it may be tempting to choose Choice A, time is actually a controlled variable (the “control”) in this experiment. We observed a phenomenon over a pre-set, controlled period of time. Really, we need to ask ourselves, “What is Briana changing?” (this will always be our independent variable) and “What is she measuring/observing?” Of course, as Briana has changed the type of bread, she’s observed a change in the amount of mold grown on each slice; so it’s clear that our independent variable is the bread type!

*Additionally, Briana has noticed that the amount of mold growth on each slice is different for each type of bread. Hence, it’s safe to say that the ‘amount of mold growth’ depends on the ‘bread type.’ Meaning: the amount of mold growth is Briana’s dependent variable!

**One final note: notice that the dependent variable sits on the x -axis of this graph, and the independent variable sits on the y -axis. This is different from what we usually see! So, it’s important that we take the “ x-axis=independent variable and y-axis=dependent variable ” trick with a grain of salt. Always read the question and the graph labels carefully!

Mia is training for a marathon. As she reads through her food & fitness tracking journal, she notices that she runs more miles on the days where she eats an apple with breakfast. What is the dependent variable in this scenario?

Amount of miles Mia runs each day

What Mia eats for breakfast

Amount of miles Mia will run in the marathon

When Mia eats an apple

The correct answer is A. In this problem, the amount of miles that Mia runs in a day depends on whether or not she eats an apple with her breakfast. We can also note that the independent variable is what Mia eats for breakfast. More specifically, it is whether or not she eats an apple with her breakfast.

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by Mometrix Test Preparation | Last Updated: June 20, 2024

9 Great Ways to Teach Variables in Science Experiments

by Katrina | Feb 17, 2024 | Pedagogy , Science | 1 comment

Science is a journey of exploration and discovery, and at the heart of every scientific experiment lies the concept of variables. Variables in science experiments are the building blocks of experimentation, allowing scientists to manipulate and measure different elements to draw meaningful conclusions.

Teaching students about variables is crucial for developing their scientific inquiry skills and fostering a deeper understanding of the scientific method.

In this blog post, we’ll explore the importance of teaching variables in science experiments, delve into the distinctions between independent, dependent, and controlled variables, and provide creative ideas on how to effectively teach these variable types.

So grab a coffee, find a comfy seat, and relax while we explore fun ways to teach variables in science experiments! 

The Importance of Teaching Variables in Science Experiments:

Foundation of Scientific Inquiry: Variables form the bedrock of the scientific method. Teaching students about variables helps them grasp the fundamental principles of scientific inquiry, enabling them to formulate hypotheses, design experiments, and draw valid conclusions.

Critical Thinking Skills: Understanding variables cultivates critical thinking skills in students. It encourages them to analyze the relationships between different factors, question assumptions, and think systematically when designing and conducting experiments.

Real-world Application: Variables are not confined to the laboratory; they exist in everyday life. Teaching students about variables equips them with the skills to critically assess and interpret the multitude of factors influencing phenomena in the real world, fostering a scientific mindset beyond the classroom.

In addition to the above, understanding scientific variables is crucial for designing an experiment and collecting valid results because variables are the building blocks of the scientific method.

A well-designed experiment involves the careful manipulation and measurement of variables to test hypotheses and draw meaningful conclusions about the relationships between different factors. Here are several reasons why a clear understanding of scientific variables is essential for the experimental process:

1. Precision and Accuracy: By identifying and defining variables, researchers can design experiments with precision and accuracy. This clarity helps ensure that the measurements and observations made during the experiment are relevant to the research question, reducing the likelihood of errors or misinterpretations.

2. Hypothesis Testing: Variables in science experiments are central to hypothesis formulation and testing. A hypothesis typically involves predicting the relationship between an independent variable (the one manipulated) and a dependent variable (the one measured). Understanding these variables is essential for constructing a hypothesis that can be tested through experimentation.

3. Controlled Experiments: Variables, especially controlled variables, enable researchers to conduct controlled experiments. By keeping certain factors constant (controlled variables) while manipulating others (independent variable), scientists can isolate the impact of the independent variable on the dependent variable. This control is essential for drawing valid conclusions about cause-and-effect relationships.

4. Reproducibility: Clear identification and understanding of variables enhance the reproducibility of experiments. When other researchers attempt to replicate an experiment, a detailed understanding of the variables involved ensures that they can accurately reproduce the conditions and obtain similar results.

5. Data Interpretation: Knowing the variables in science experiments allows for a more accurate interpretation of the collected data. Researchers can attribute changes in the dependent variable to the manipulation of the independent variable and rule out alternative explanations. This is crucial for drawing reliable conclusions from the experimental results.

6. Elimination of Confounding Factors: Without a proper understanding of variables, experiments are susceptible to confounding factors—unintended variables that may influence the results. Through careful consideration of all relevant variables, researchers can minimize the impact of confounding factors and increase the internal validity of their experiments.

7. Optimization of Experimental Design: Understanding variables in science experiments helps researchers optimize the design of their experiments. They can choose the most relevant and influential variables to manipulate and measure, ensuring that the experiment is focused on addressing the specific research question.

8. Applicability to Real-world Situations: A thorough understanding of variables enhances the applicability of experimental results to real-world situations. It allows researchers to draw connections between laboratory findings and broader phenomena, contributing to the advancement of scientific knowledge and its practical applications.

The Different Types of Variables in Science Experiments:

There are 3 main types of variables in science experiments; independent, dependent, and controlled variables.

1. Independent Variable:

The independent variable is the factor that is deliberately manipulated or changed in an experiment. The independent variable affects the dependent variable (the one being measured).

Example : In a plant growth experiment, the amount of sunlight the plants receive can be the independent variable. Researchers might expose one group of plants to more sunlight than another group.

2. Dependent Variable:

The dependent variable is the outcome or response that is measured in an experiment. It depends on the changes made to the independent variable.

Example : In the same plant growth experiment, the height of the plants would be the dependent variable. This is what researchers would measure to determine the effect of sunlight on plant growth.

3. Controlled Variable:

Controlled variables, also called constant variables, are the factors in an experiment that are kept constant to ensure that any observed changes in the dependent variable are a result of the manipulation of the independent variable. These are not to be confused with control groups.

In a scientific experiment in chemistry, a control group is a crucial element that serves as a baseline for comparison. The control group is designed to remain unchanged or unaffected by the independent variable, which is the variable being manipulated in the experiment.

The purpose of including a control group is to provide a reference point against which the experimental results can be compared, helping scientists determine whether the observed effects are a result of the independent variable or other external factors.

Example : In the plant growth experiment, factors like soil type, amount of water, type of plant and temperature would be control variables. Keeping these constant ensures that any differences in plant height can be attributed to changes in sunlight.

Science variables in science experiments

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Best resources for reviewing variables in science experiments:

If you’re short on time and would rather buy your resources, then I’ve compiled a list of my favorite resources for teaching and reviewing variables in science experiments below. While there is nothing better than actually doing science experiments, this isn’t feasible every lesson and these resources are great for consolidation of learning:

1. FREE Science Variables Posters : These are perfect as a visual aide in your classroom while also providing lab decorations! Print in A4 or A3 size to make an impact.

2. Variable scenarios worksheet printable : Get your students thinking about variable with these train your pet dragon themed scenarios. Students identify the independent variable, dependent variable and controlled variables in each scenario.

3. Variable Valentines scenarios worksheet printable : Get your students thinking about variables with these cupid Valentine’s Day scenarios. Students identify the independent variable, dependent variable and controlled variables in each scenario.

4. Variable Halloween scenarios worksheet printable : Spook your students with these Halloween themed scenarios. Students identify the independent variable, dependent variable and controlled variables in each scenario.

5. Scientific Method Digital Escape Room : Review all parts of the scientific method with this fun (zero prep) digital escape room! 

6. Scientific Method Stations Printable or Sub Lesson : The worst part of being a teacher? Having to still work when you are sick! This science sub lesson plan includes a fully editable lesson plan designed for a substitute teacher to take, including differentiated student worksheets and full teacher answers. This lesson involves learning about all parts of the scientific method, including variables.

Digital Lab Equipment Escape Room Middle School Science

Scientific Method Digital Escape Room Science Middle School

Science Graphing Skills Escape Room Middle School

9 teaching strategies for variables in science experiments.

To help engage students in learning about the different types of scientific variables, it is important to include a range of activities and teaching strategies. Here are some suggestions:

1. Hands-on Experiments: Conducting hands-on experiments is one of the most effective ways to teach students about variables. Provide students with the opportunity to design and conduct their experiments, manipulating and measuring variables to observe outcomes.

Easy science experiments you could include might relate to student heart rate (e.g. before and after exercise), type of ball vs height it bounces, amount of sunlight on the growth of a plant, the strength of an electromagnet (copper wire around a nail) vs the number of coils.

Change things up by sometimes having students identify the independent variable, dependent variable and controlled variables before the experiment, or sometimes afterwards.

Consolidate by graphing results and reinforcing that the independent variable goes alone the x-axis while the dependent variable goes on the y-axis.

2. Teacher Demonstrations:

Use demonstrations to illustrate the concepts of independent, dependent, and controlled variables. For instance, use a simple chemical reaction where the amount of reactant (independent variable) influences the amount of product formed (dependent variable), with temperature and pressure controlled.

3. Case Studies:

Introduce case studies that highlight real-world applications of variables in science experiments. Discuss famous experiments or breakthroughs in science where variables played a crucial role. This approach helps students connect theoretical knowledge to practical situations.

4. Imaginary Situations:

Spark student curiosity and test their understanding of the concept of variables in science experiments by providing imaginary situations or contexts for students to apply their knowledge. Some of my favorites to use are this train your pet dragon and Halloween themed variables in science worksheets.

5. Variable Sorting Activities:

Engage students with sorting activities where they categorize different variables in science experiments into independent, dependent, and controlled variables. This hands-on approach encourages active learning and reinforces their understanding of variable types.

6. Visual Aids:

Utilize visual aids such as charts, graphs, and diagrams to visually represent the relationships between variables. Visualizations can make abstract concepts more tangible and aid in the comprehension of complex ideas.

7. Technology Integration:

Leverage technology to enhance variable teaching. Virtual simulations and interactive apps can provide a dynamic platform for students to manipulate variables in a controlled environment, fostering a deeper understanding of the cause-and-effect relationships.

Websites such as   Phet   are a great tool to use to model these types of scientific experiments and to identify and manipulate the different variables

8. Group Discussions:

Encourage group discussions where students can share their insights and experiences related to variables in science experiments. This collaborative approach promotes peer learning and allows students to learn from each other’s perspectives.

9. Digital Escape Rooms:

Reinforce learning by using a fun interactive activity like this scientific method digital escape room.

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The Musculoskeletal System Worksheet Stations

Engaging Cardiovascular System Worksheet Stations

Teaching variables in science experiments is an essential component of science education, laying the groundwork for critical thinking, inquiry skills, and a lifelong appreciation for the scientific method.

By emphasizing the distinctions between independent, dependent, and controlled variables and employing creative teaching strategies, educators can inspire students to become curious, analytical, and scientifically literate individuals. 

What are your favorite ways to engage students in learning about the different types of variables in science experiments? Comment below!

Note: Always consult your school’s specific safety guidelines and policies, and seek guidance from experienced colleagues or administrators when in doubt about safety protocols. 

Teaching variables in science experiments

About the Author

Katrina Harte is a multi-award winning educator from Sydney, Australia who specialises in creating resources that support teachers and engage students.

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How to Identify Dependent and Independent Variables

Last Updated: June 29, 2024 Fact Checked

This article was co-authored by Michael Simpson, PhD . Dr. Michael Simpson (Mike) is a Registered Professional Biologist in British Columbia, Canada. He has over 20 years of experience in ecology research and professional practice in Britain and North America, with an emphasis on plants and biological diversity. Mike also specializes in science communication and providing education and technical support for ecology projects. Mike received a BSc with honors in Ecology and an MA in Society, Science, and Nature from The University of Lancaster in England as well as a Ph.D. from the University of Alberta. He has worked in British, North American, and South American ecosystems, and with First Nations communities, non-profits, government, academia, and industry. There are 10 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 138,058 times.

Whether you’re conducting an experiment or learning algebra, understanding the relationship between independent and dependent variables is a valuable skill. Learning the difference between them can be tricky at first, but you’ll get the hang of it in no time.

Understanding Independent and Dependent Variables

• For example, if a researcher wants to see how well different doses of a medication work, the dose is the independent variable.
• Suppose you want to see if studying more improves your test scores. The amount of time you spend studying is the independent variable.

• Say a researcher is testing an allergy medication. Allergy relief after taking the dose is the dependent variable, or the outcome caused by taking the medicine.

Tip: When you encounter variables, plug them into this sentence: “ Independent variable causes Dependent Variable , but it isn't possible that Dependent Variable could cause Independent Variable .

For example: “A 5 mg dose of medication causes allergy relief, but it isn’t possible that allergy relief could cause a 5 mg dose of medication.”

Identifying Variables in Equations

• The $3 per chore is a constant. Your parents set that in stone, and that number isn't going to change. On the other hand, the number of chores you do and the total amount of money you earn aren't constant. They're variables that you want to measure.
• To set up an equation, use letters to represent the chores you do and the money you'll earn. Let t represent the total amount of money you earn and n stand for the number of chores you do.

• Notice that the amount of money you'll earn depends on the number of chores to do. Since it depends on other variables, it's the dependent variable.

Graphing Independent and Dependent Variables

• Say you sell apples and want to see how advertising affects your sales. The amount of money you spent in a month on advertising is the independent variable, or the factor that causes the effect you’re trying to understand. The number of apples you sold that month is the dependent variable.

• Suppose you’re trying to see if advertising more increases the number of apples you sold. Divide the x-axis into units to measure your monthly advertising budget.
• If you’ve spent between $0 and $500 a month in the last year on advertising, draw 10 dashes along the x-axis. Label the left end of the line “$0.” Then label each dash with a dollar amount in $50 increments ($50, $100, $150, and so on) until you’ve reached the last dash, or “$500.”

• Suppose your monthly apple sales have ranged between 60 and 250 over the last year. Draw 10 dashes across the y-axis, label the first “50,” and label the rest of the dashes in increments of 25 (50, 75, 100, and so on), until you’ve written 275 next to the last dash.

• For instance, if you spent $350 on advertising last month, find the dash labeled “350” on the x-axis. If last month’s apple sales totaled 225, find the dash labeled “225” on the y-axis. Draw a dot at the point at the graph coordinate ($350, 225), then continue graphing points for the rest of your monthly numbers.

• For example, say you’ve graphed your advertising expenses and monthly apple sales, and the dots are arranged in an upward sloped line. This means that your monthly sales were higher when you spent more on advertising.

Expert Q&A

You Might Also Like

• ↑ Michael Simpson, PhD. Registered Professional Biologist. Expert Interview. 25 June 2021.
• ↑ https://researchbasics.education.uconn.edu/variables/
• ↑ https://libguides.usc.edu/writingguide/variables
• ↑ https://nces.ed.gov/nceskids/help/user_guide/graph/variables.asp
• ↑ https://www.khanacademy.org/math/algebra/introduction-to-algebra/alg1-dependent-independent/e/dependent-and-independent-variables
• ↑ https://www.mathsisfun.com/algebra/equations-solving.html
• ↑ https://www.khanacademy.org/math/pre-algebra/pre-algebra-equations-expressions/pre-algebra-dependent-independent/a/dependent-and-independent-variables-review
• ↑ https://www2.nau.edu/lrm22/lessons/graph_tips/graph_tips.html
• ↑ https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-equations-and-inequalities/cc-6th-dependent-independent/v/dependent-and-independent-variables-exercise-example-2
• ↑ https://nces.ed.gov/nceskids/help/user_guide/graph/line.asp

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Identification of Variables

Learn to identify the independent variable and the dependent variable in an experiment with this interactive tutorial.

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Difference Between Independent and Dependent Variables

The independent and dependent variables are the two main types of variables in a science experiment. A variable is anything you can observe, measure, and record. This includes measurements, colors, sounds, presence or absence of an event, etc.

The independent variable is the one factor you change to test its effects on the dependent variable . In other words, the dependent variable “depends” on the independent variable. The independent variable is sometimes called the controlled variable, while the dependent variable may be called the experimental or responding variable.

• The independent variable is the one you control or manipulate. The dependent variable is the one that responds and that you measure.
• The independent variable is the cause, while the dependent variable is the effect.
• Graph the independent variable on the x-axis. Graph the dependent variable on the y-axis.

How to Tell the Independent and Dependent Variable Apart

Both the independent and dependent variables may change during an experiment, but the independent variable is the one you control, while the dependent variable is one you measure in response to this change. The easiest way to tell the two variables apart is to phrase the experiment in terms of an “if-then” or “cause and effect” statement. If you change the independent variable, then you measure its effect on the dependent variable. The cause is the independent variable, while the effect is the dependent variable. If you state “time spent studying affect grades” (independent variables determines dependent variable), the statement makes sense. If your cause and effect statement is in the wrong order (grades determine time spent studying), it doesn’t make sense.

Sometimes the independent variable is easy to identify. Time and age are almost always the independent variable in an experiment. You can measure them, but you can’t control any factor to change them.

Ask yourself these questions to help tell the two variables apart:

Independent Variable

• Can you control or manipulate this variable?
• Does this variable come first in time?
• Are you trying to tell whether this variable affects an outcome or answers a question?

Dependent Variable

• Does this variable depend on another variable in the experiment?
• Do you measure this variable after controlling another factor?

Examples of Independent and Dependent Variables

For example, if you want to see whether changing dog food affects your pet’s weight, you can phrase the experiment as, “If I change dog food, then my dog’s weight may change.” The independent variable is the type of dog food, while the dog’s weight is the dependent variable.

In an experiment to test whether a drug is an effective pain reliever, the presence, absence, or dose of the drug is the variable you control (the independent variable), while the pain level of the patient is the dependent variable.

In an experiment to determine whether ice cube shapes determine how quickly ice cubes melt, the independent variable is the shape of the ice cube, while the time it takes to melt is the dependent variable.

If you want to see if the temperature of a classroom affects test score, the temperature is the independent variable. Test scores are the dependent variable.

Graphing Independent and Dependent Variables With DRYMIX

By convention, the independent variable is plotted on the x-axis of a graph, while the dependent variable is plotted on the y-axis. Use the DRY MIX acronym to remember the variables:

D is the dependent variable R is the variable that responds Y is the y-axis or vertical axis

M is the manipulated or controlled variable I is the independent variable X is the x-axis or horizontal axis

• Carlson, Robert (2006).  A Concrete Introduction to Real Analysis . CRC Press.
• Edwards, Joseph (1892).  An Elementary Treatise on the Differential Calculus  (2nd ed.). London: MacMillan and Co.
• Everitt, B. S. (2002).  The Cambridge Dictionary of Statistics  (2nd ed.). Cambridge UP. ISBN 0-521-81099-X.
• Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments. Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
• Quine, Willard V. (1960). “ Variables Explained Away “.  Proceedings of the American Philosophical Society . American Philosophical Society. 104 (3): 343–347. 

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• Identify Variables in a Scientific Investigation

Understanding the Difference Between Independent, Dependent and Control Variables is Crucial!

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EdPlace's Year 9 Home Learning Science Lesson: Identify Variables in an Investigation

Looking for short lessons to keep your child engaged and learning? Our experienced team of teachers have created English, maths and science lessons for the home, so your child can learn no matter where they are.  And, as all activities are self-marked, you really can encourage your child to be an independent learner.  

Get them started on the lesson below and then jump into our teacher-created activities to practice what they've learnt. We've recommended five to ensure they feel secure in their knowledge - 5-a-day helps keeps the learning loss at bay (or so we think!).

Are they keen to start practising straight away? Head to the bottom of the page to find the activities. 

Now...onto the lesson!

Are You Up to Speed with Variables?

Independent, dependent and control variables. Never heard of them? Well, grab yourself a cuppa, a biscuit or two, and prepare to feel confident enough to teach it to your young scientist standing on your head with a blindfold on! Working scientifically is a key area within the national science curriculum, from primary all the way up to A-level. This area of study concerns skills which relate to practical investigations, for example planning an experiment, carrying it out, writing up conclusions, as well as processing results mathematically. However, identifying variables in scientific investigations can be a cause of much confusion. 

By the end of this 5 step guide, your EdPlace team are confident that your child will be able to:

1)  Understand the different kinds of variables

2) Apply this knowledge to a practical investigation

3) Explain  this knowledge back to you (If they've really cracked it!)

Step 1: Learning the Lingo!

Before we get our hands dirty with practicals it's crucial that Year 9 students are clear on the following terminology. Below are three key terms and their definitions which we shall focus on in this topic.

Independent variable -  the one condition that is changed during a scientific experiment, by the scientist. The experimenter alters the independent variable in order to test the dependent variable.

Dependent variable - the one condition that is observed or measured during a scientific experiment. 

Control variable -  these are the elements that are kept the same during a scientific experiment. Any change to a controlled variable would invalidate the results.

Step 2: Why Must We Ensure Our Scientific Experiments are Fair?

Science experiments, or investigations, are the part of science lessons that students enjoy most! It gives them a chance to witness science at work beyond textbooks and worksheets, and really get stuck in. So much of science centres things you cannot see, so investigations enable teachers to bring the subject to life. 

Scientific investigations always have a purpose to them – they involve observations and measurements being taken. They involve conditions being tweaked, seeing how these changes impact the outcome. Then, from the results, we collect we can draw conclusions. These are the fundamentals of scientific study - investigations allow us to advance scientific knowledge and better our understanding of the world and its workings.

Children are taught as early as Year 1 that we must make sure any experiments are a fair test. For example, if we conduct an experiment looking at whether boys run faster than girls in a race, we must make the test fair. We must make sure the distance they run is the same, the conditions are the same (i.e. not make the girls run with only one shoe on) and the way we determine each participant's speed is the same (i.e. not count in our heads for the boys, but use a stopwatch to measure the girls' speed). This understanding of fairness is our foundation for learning about variables, which we shall look at now.

Step 3: Getting to Grips with Variables

The elements that change in an experiment are called  variables . A variable is any factor, trait, or condition that can exist in differing amounts or types. An experiment usually has three kinds of variables: independent , dependent , and controlled . Let's use a basic experiment as an example: A group of students want to find out whether temperature affects how quickly sugar dissolves . They set up an experiment with four beakers of water, each at a different temperature. They add a spoonful of sugar to each, sir each beaker once only, and timed how long it took for the sugar to disappear.

Let's quickly refresh our memory:

Independent variable -  the one condition that is changed during a scientific experiment, by the scientist. There is only ever one independent variable. 

Dependent variable - the one condition that is observed or measured during a scientific experiment. There is only one dependent variable. 

Control variable -  these are the elements that are kept the same during a scientific experiment. There can be multiple control variables. Any change to a controlled variable would invalidate the results, so it's really important that they are kept the same throughout. 

So, using our example, we now should be able to identify the variables ourselves...

Independent variable = the temperature of the water

Dependent variable = the time it takes for all the sugar to disappear/dissolve

Control variables = the volume of water in beakers, the size of the beaker, the amount of sugar, the number of times it is stirred, the type of sugar used.

An easy way to think of independent and dependent variables is, when you're conducting an experiment, the independent variable is what you change, and the dependent variable is what changes because of that. You can also think of the independent variable as the cause and the dependent variable as the effect.

Let’s attempt another example together. Imagine you want to see which type of fertiliser helps plants grow fastest, so you add a different brand of fertiliser to each plant and see how tall they grow.

Independent variable = the type of fertiliser given to the plant

Dependent variable = plant height

Control variables = the type of plant used, the amount of fertiliser given, the time given to grow. And all other conditions kept the same between each plant e.g. the amount of water each plant receives, the temperature of the room, the amount of sunlight etc.

Why not try executing your own investigation? You could look at how the mass of a toy attached to a parachute affects how long it takes to fall. This will give you an opportunity to make a parachute (perhaps using a piece of scrap material and some string, tried to various toys such as a toy car, a Playmobil person, a cuddly toy). You will also need a set of scales to measure the mass of each toy. Remember to use the same parachute each time! As you’re doing the investigation you can identify what are the independent and dependent variables, and what elements are your control variables.

Step 4: Put Your Knowledge to the Test!

Ok, now its time to see whether all this information is sinking in. Answer the following questions to test your understanding of variables.

1. Sally is performing a test in which she is trying to see if plants can grow when given fizzy drinks instead of water. She gives one plant water and a second identical plant the same amount of fizzy drink for two weeks. What is the independent variable?

a) The plants

b) The amount of liquid

c) The type of liquid

2. Mark carried out an investigation to see how the strength of an electromagnet coil changes with the number of coils.  What is the dependent variable?

3. April and Harry wanted to find the best pen. They decided to put a few to the test and measure which pen type lasted the longest before running out. They each chose a pen, Harry a ballpoint pen and April a fountain pen. Both used their pen to write with at school from Monday morning, and by Wednesday, April’s had run out. They concluded that ballpoint pens were the best. 

a) What was the independent variable?

b) What was the dependent variable?

c) Why is the experiment not reliable enough to base a conclusion on? i.e.  What control variables should they have used?  

Ready for a trickier one that will really push you?

4.  When magnesium is added to hydrochloric acid, how does acid concentration affect temperature change? 

Step 5: Let's apply your knowledge

Now that we've moved through this lesson together and put this knowledge to the test with practice questions, why not have ago tackling some EdPlace activities? Assign your child the following five activities, in order, to really consolidate their understanding. This way, you will be able to identify potential areas of concern or, ideally, demonstrate your child's confidence and comprehension! All activities are created by teachers and automatically marked. Plus, with an EdPlace subscription, we can automatically progress your child at a level that's right for them. Sending you progress reports along the way so you can track and measure progress, together - brilliant! 

Activity 1 - Evaluate Scientific Investigations

Activity 2 - Measure Accurately

Activity 3 - Draw and Evaluate Conclusions

Activity 4 - Plan an Investigation: Hypothesis and Method

Activity 5 - End of Key Stage 3 Assessment: Biology

1) The type of liquid (c)

2) The strength of the electromagnet

3a) The type of pen 

3b) The time taken for each pen to run out

3c) The experiment is unreliable because so many variables were left uncontrolled. April and Harry should have controlled the amount of writing produced by each person, even the size of writing would have impacted how quickly each pen ran out. The amount of ink in each pen when they started should also have been controlled.

Keep going! Looking for more activities, different subjects or year groups?

Click the button below to view the EdPlace English, maths, science and 11+ activity library

All English, maths and science from Year 1 - GCSE

• Home Education
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• Key Stage 3

WRITTEN BY: Ms Joy – SCIENCE TEACHER

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