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Dependent & Independent Variables in Science Experiments

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Understanding how variables in science experiments work is an important skill for our students to understand. We do a lot of science experiments in my classroom, and knowing how different factors can change the outcome of a scientific experiment is always something I want them to be able to discover and explain. It’s also great practice for the scientific method. Here are some of the best ways to teach dependent and independent variables in your science classroom.

​VARIABLES IN SCIENCE EXPERIMENTS: WHAT ARE THEY?

Here are definitions you can use with your students, using a plant growth experiment as a base:

• Example: If you are testing how different amounts of water affect plant growth, the amount of water is the independent variable because it’s what you change in your experiment.
• Example: In the plant experiment, the growth of the plant is the dependent variable because it’s what you measure to see how much the plant has grown based on the different amounts of water.

My  Independent and Dependent Variables Resource has a foldable, interactive vocabulary activity that helps students understand the concept of variables.  In the resource, students also define what control variables are.

​It’s important for our students to know the variable that we are changing and the variables that occur because of that one change. It’s also  so  important to make sure the kids understand how important changing only one thing is. We need to know what caused the outcome of the experiment, and that’s difficult if we change different variables.

DESIGNING EXPERIMENTS

Once students understand what variables are, we need to help them put this new vocabulary into action. That’s where experiments come in! I like to start with a premade experiment that guide students through how variables work in a real-world context. An easy experiment that I like to use with my students is  W hat Will Make Ice Melt the Fastest? . Students work with three different materials that we have on hand in class, and they predict which substance will make ice melt the fastest. I like to use sand, water, salt, sugar, or anything similar. I also make sure students know we need a control group to see what happens when no substance is applied to the ice.

FOCUS ON THE VARIABLES

Students can sometimes get lost in the steps of an experiment and forget what brought the results about. For this reason, I make sure that my students can communicate to each other what the variables were and, more importantly,  why  each variable exists. For example, in the plant growth experiment, the goal is for my students to be able to explain that:

• the independent variable is the amount of water we’re using, because we are changing the amount on purpose;
• the dependent variable is the plant’s growth, because that will change based on the water we give it;
• the controlled variables are anything we don’t intend to change, which in this case could be the type of soil used, the type of plant used, the amount of light each plant gets, the type of liquid (we always use the same tap water), and so on.

To keep the focus even stronger, the students know that their exit ticket for the class will be for them to explain what an independent, dependent, and controlled variable is. You can have students define in it general, or you can have them provide examples based on the results of the experiment.

ANALYZE THE DATA

Once my students have correctly identified the different types of variables in an experiment, we analyze the data we collected. I want them to understand, and then be able to explain to someone else, how the independent variable affects the dependent variable. For example, in my  What Will Make Ice Melt the Fastest?   lab, students conclude that the salt melted the ice fastest. The constant variables were anything we didn’t change, such as how long we timed them melting and the temperature of the room. The final outcome of an experiment is important, and knowing the why behind the outcome is important too.

Understanding these variables helps students design good experiments and understand the results better when they go off and create their own scientific investigations. When our students know what we are changing (independent variable) and what we are measuring (dependent variable), they can make better observations and conclusions. Being able to analyze the results of an experiment is a great critical thinking developer, and students pick up scientific inquiry skills they can use throughout the year.

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• Knowledge Base

Methodology

• 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.

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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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Scientific Variable

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A variable is any factor that can be changed or controlled. In math, a variable is a quantity that can assume any value from a set of values. A scientific variable is a little more complicated, plus there are different types of scientific variables.

Scientific variables are associated with the scientific method . Variables are things that are controlled and measured as part of a scientific experiment. There are three main types of variables:

Controlled Variables

As the name implies, controlled variables are factors that are controlled or held constant throughout an investigation. They are kept unchanging so that they won't influence the outcome of the experiment by changing. However, they do have an impact on the experiment. For example, if you are measuring whether plants grow better when watered with milk or water, one of the controlled variables might be the amount of light that is given to the plants. Even though the value may be held constant throughout the experiment, it is important to note the condition of this variable. You would expect the growth of the plant might be different in sunlight as compared with darkness, right? Tracking controlled variables makes it easier to replicate an experiment. Sometimes the effect of a variable comes as a surprise, leading to a new experiment.

Independent Variable

The independent variable is the one factor that you purposely change in an experiment. For example, in an experiment looking at whether plant growth is affected by watering with water or milk the independent variable is the substance used to water the plants. Many experiments are based on an "if-then" scenario, where the researcher measures what happens if a variable is changed. The "if" part of the experiment is the independent variable.

Dependent Variable

The dependent variable is the variable that you are measuring in order to determine whether or not it is affected by a change in the independent variable. In the plant experiment, the growth of the plant is the dependent variable. In an "if-then" experiment, the response to a change refers to the dependent variable. Its value depends on the status of the independent variable.

Plotting a Graph of Variables

When you plot a graph of your data, the x-axis is the independent variable and the y-axis is the dependent variable . In our example, the height of the plant would be recorded on the y-axis while the substance used to water the plants would be recorded on the x-axis. In this case, a bar graph would be an appropriate way to present the data.

• Scientific Method Flow Chart
• Six Steps of the Scientific Method
• What Is a Hypothesis? (Science)
• What Are the Elements of a Good Hypothesis?
• Null Hypothesis Examples
• Scientific Method Vocabulary Terms
• What Is a Testable Hypothesis?
• Understanding Simple vs Controlled Experiments
• DRY MIX Experiment Variables Acronym
• The Role of a Controlled Variable in an Experiment
• What Is the Difference Between a Control Variable and Control Group?
• Scientific Hypothesis Examples
• What Is a Controlled Experiment?
• What Are Examples of a Hypothesis?
• What Is an Experimental Constant?
• Random Error vs. Systematic Error

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.

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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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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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Ideas for Controlled Variable Science Projects

Science Projects With Three Variables for Kids in Fifth Grade

Many science projects investigate a combination of independent and controlled variables to see what happens as a result - the dependent variable. To get reliable results from your experiments, you change the independent variables carefully and the controlled variables as little as possible; this ensures that only the things you're interested in affect your experimental results.

Does Sugar Dissolve More Quickly in Warm or Cool Water?

Heat a cup of water while allowing another cup of water to remain cool. Dissolve one teaspoon of sugar in each cup of water. The controlled variable would be the number of times and the pressure used to stir the mixture because added motion of the water may or may not dissolve the sugar more quickly whether the water is warm or cool. Record the amount of undissolved sugar in the bottom of the container.

Does a Plant Grow Better in Direct or Indirect Sunlight?

A science project involving plants has controlled variables in the amount of water given to each plant and the amount and kind of soil in which the plant is living. Place one plant in direct sunlight and the other in a shaded area or indoors to conduct the science experiment. Record daily results in the height of the plant.

Will a Baby Bunny Grow Bigger When Fed Rabbit Food or Fresh Vegetables?

Two rabbits, ideally from the same litter, can be used to conduct a classroom experiment. Give each rabbit a different diet: one of only fresh vegetables such as lettuce, carrots and celery; feed the other rabbit pellets from the pet store. The controlled variable in this experiment would be the weight in food each rabbit receives even though the type of food is different. Record the height, weight and length of the two rabbits each week.

Which Will Clean a Penny Faster, Water or Vinegar?

In two glass containers, place one cup of distilled water in one and white vinegar in the other. Carefully drop a dirty penny into each container of liquid and record the changes in the penny's appearance over the course of one week. The controlled variable is in the amount of liquid used to clean each penny.

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Government of Canada invests $2.9 million in 8 environmental education projects across the country

From: Environment and Climate Change Canada

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On September 13, 2024, Environment and Climate Change Canada announced that 8 Canadian organizations will receive a total of $2.9 million for their projects dedicated to environmental education and climate literacy. The projects contribute to the Government of Canada's strategy to inform, engage, and mobilize Canadians for climate action. The funded projects include:

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What Is a Control Variable? Definition and Examples

A control variable is any factor that is controlled or held constant during an experiment . For this reason, it’s also known as a controlled variable or a constant variable. A single experiment may contain many control variables . Unlike the independent and dependent variables , control variables aren’t a part of the experiment, but they are important because they could affect the outcome. Take a look at the difference between a control variable and control group and see examples of control variables.

Importance of Control Variables

Remember, the independent variable is the one you change, the dependent variable is the one you measure in response to this change, and the control variables are any other factors you control or hold constant so that they can’t influence the experiment. Control variables are important because:

• They make it easier to reproduce the experiment.
• The increase confidence in the outcome of the experiment.

For example, if you conducted an experiment examining the effect of the color of light on plant growth, but you didn’t control temperature, it might affect the outcome. One light source might be hotter than the other, affecting plant growth. This could lead you to incorrectly accept or reject your hypothesis. As another example, say you did control the temperature. If you did not report this temperature in your “methods” section, another researcher might have trouble reproducing your results. What if you conducted your experiment at 15 °C. Would you expect the same results at 5 °C or 35 5 °C? Sometimes the potential effect of a control variable can lead to a new experiment!

Sometimes you think you have controlled everything except the independent variable, but still get strange results. This could be due to what is called a “ confounding variable .” Examples of confounding variables could be humidity, magnetism, and vibration. Sometimes you can identify a confounding variable and turn it into a control variable. Other times, confounding variables cannot be detected or controlled.

Control Variable vs Control Group

A control group is different from a control variable. You expose a control group to all the same conditions as the experimental group, except you change the independent variable in the experimental group. Both the control group and experimental group should have the same control variables.

Control Variable Examples

Anything you can measure or control that is not the independent variable or dependent variable has potential to be a control variable. Examples of common control variables include:

• Duration of the experiment
• Size and composition of containers
• Temperature
• Sample volume
• Experimental technique
• Chemical purity or manufacturer
• Species (in biological experiments)

For example, consider an experiment testing whether a certain supplement affects cattle weight gain. The independent variable is the supplement, while the dependent variable is cattle weight. A typical control group would consist of cattle not given the supplement, while the cattle in the experimental group would receive the supplement. Examples of control variables in this experiment could include the age of the cattle, their breed, whether they are male or female, the amount of supplement, the way the supplement is administered, how often the supplement is administered, the type of feed given to the cattle, the temperature, the water supply, the time of year, and the method used to record weight. There may be other control variables, too. Sometimes you can’t actually control a control variable, but conditions should be the same for both the control and experimental groups. For example, if the cattle are free-range, weather might change from day to day, but both groups have the same experience. When you take data, be sure to record control variables along with the independent and dependent variable.

• Box, George E.P.; Hunter, William G.; Hunter, J. Stuart (1978). Statistics for Experimenters : An Introduction to Design, Data Analysis, and Model Building . New York: Wiley. ISBN 978-0-471-09315-2.
• Giri, Narayan C.; Das, M. N. (1979). Design and Analysis of Experiments . New York, N.Y: Wiley. ISBN 9780852269145.
• Stigler, Stephen M. (November 1992). “A Historical View of Statistical Concepts in Psychology and Educational Research”. American Journal of Education . 101 (1): 60–70. doi: 10.1086/444032

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