experiment with variables

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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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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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Independent and Dependent Variables Examples

The independent and dependent variables are key to any scientific experiment, but how do you tell them apart? Here are the definitions of independent and dependent variables, examples of each type, and tips for telling them apart and graphing them.

Independent Variable

The independent variable is the factor the researcher changes or controls in an experiment. It is called independent because it does not depend on any other variable. The independent variable may be called the “controlled variable” because it is the one that is changed or controlled. This is different from the “ control variable ,” which is variable that is held constant so it won’t influence the outcome of the experiment.

Dependent Variable

The dependent variable is the factor that changes in response to the independent variable. It is the variable that you measure in an experiment. The dependent variable may be called the “responding variable.”

Examples of Independent and Dependent Variables

Here are several examples of independent and dependent variables in experiments:

• In a study to determine whether how long a student sleeps affects test scores, the independent variable is the length of time spent sleeping while the dependent variable is the test score.
• You want to know which brand of fertilizer is best for your plants. The brand of fertilizer is the independent variable. The health of the plants (height, amount and size of flowers and fruit, color) is the dependent variable.
• You want to compare brands of paper towels, to see which holds the most liquid. The independent variable is the brand of paper towel. The dependent variable is the volume of liquid absorbed by the paper towel.
• You suspect the amount of television a person watches is related to their age. Age is the independent variable. How many minutes or hours of television a person watches is the dependent variable.
• You think rising sea temperatures might affect the amount of algae in the water. The water temperature is the independent variable. The mass of algae is the dependent variable.
• In an experiment to determine how far people can see into the infrared part of the spectrum, the wavelength of light is the independent variable and whether the light is observed is the dependent variable.
• If you want to know whether caffeine affects your appetite, the presence/absence or amount of caffeine is the independent variable. Appetite is the dependent variable.
• You want to know which brand of microwave popcorn pops the best. The brand of popcorn is the independent variable. The number of popped kernels is the dependent variable. Of course, you could also measure the number of unpopped kernels instead.
• You want to determine whether a chemical is essential for rat nutrition, so you design an experiment. The presence/absence of the chemical is the independent variable. The health of the rat (whether it lives and reproduces) is the dependent variable. A follow-up experiment might determine how much of the chemical is needed. Here, the amount of chemical is the independent variable and the rat health is the dependent variable.

How to Tell the Independent and Dependent Variable Apart

If you’re having trouble identifying the independent and dependent variable, here are a few ways to tell them apart. First, remember the dependent variable depends on the independent variable. It helps to write out the variables as an if-then or cause-and-effect sentence that shows the independent variable causes an effect on the dependent variable. If you mix up the variables, the sentence won’t make sense. Example : The amount of eat (independent variable) affects how much you weigh (dependent variable).

This makes sense, but if you write the sentence the other way, you can tell it’s incorrect: Example : How much you weigh affects how much you eat. (Well, it could make sense, but you can see it’s an entirely different experiment.) If-then statements also work: Example : If you change the color of light (independent variable), then it affects plant growth (dependent variable). Switching the variables makes no sense: Example : If plant growth rate changes, then it affects the color of light. Sometimes you don’t control either variable, like when you gather data to see if there is a relationship between two factors. This can make identifying the variables a bit trickier, but establishing a logical cause and effect relationship helps: Example : If you increase age (independent variable), then average salary increases (dependent variable). If you switch them, the statement doesn’t make sense: Example : If you increase salary, then age increases.

How to Graph Independent and Dependent Variables

Plot or graph independent and dependent variables using the standard method. The independent variable is the x-axis, while the dependent variable is the y-axis. Remember the acronym DRY MIX to keep the variables straight: D = Dependent variable R = Responding variable/ Y = Graph on the y-axis or vertical axis M = Manipulated variable I = Independent variable X = Graph on the x-axis or horizontal axis

• Babbie, Earl R. (2009). The Practice of Social Research (12th ed.) Wadsworth Publishing. ISBN 0-495-59841-0.
• di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 978-0-521-29925-1.
• Gauch, Hugh G. Jr. (2003). Scientific Method in Practice . Cambridge University Press. ISBN 978-0-521-01708-4.
• Popper, Karl R. (2003). Conjectures and Refutations: The Growth of Scientific Knowledge . Routledge. ISBN 0-415-28594-1.

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Biology archive

Course: biology archive   >   unit 1.

• The scientific method

Controlled experiments

• The scientific method and experimental design

Introduction

How are hypotheses tested.

• One pot of seeds gets watered every afternoon.
• The other pot of seeds doesn't get any water at all.

Control and experimental groups

Independent and dependent variables, independent variables, dependent variables, variability and repetition, controlled experiment case study: co 2 ‍   and coral bleaching.

• What your control and experimental groups would be
• What your independent and dependent variables would be
• What results you would predict in each group

Experimental setup

• Some corals were grown in tanks of normal seawater, which is not very acidic ( pH ‍   around 8.2 ‍   ). The corals in these tanks served as the control group .
• Other corals were grown in tanks of seawater that were more acidic than usual due to addition of CO 2 ‍   . One set of tanks was medium-acidity ( pH ‍   about 7.9 ‍   ), while another set was high-acidity ( pH ‍   about 7.65 ‍   ). Both the medium-acidity and high-acidity groups were experimental groups .
• In this experiment, the independent variable was the acidity ( pH ‍   ) of the seawater. The dependent variable was the degree of bleaching of the corals.
• The researchers used a large sample size and repeated their experiment. Each tank held 5 ‍   fragments of coral, and there were 5 ‍   identical tanks for each group (control, medium-acidity, and high-acidity). Note: None of these tanks was "acidic" on an absolute scale. That is, the pH ‍   values were all above the neutral pH ‍   of 7.0 ‍   . However, the two groups of experimental tanks were moderately and highly acidic to the corals , that is, relative to their natural habitat of plain seawater.

Analyzing the results

Non-experimental hypothesis tests, case study: coral bleaching and temperature, attribution:, works cited:.

• Hoegh-Guldberg, O. (1999). Climate change, coral bleaching, and the future of the world's coral reefs. Mar. Freshwater Res. , 50 , 839-866. Retrieved from www.reef.edu.au/climate/Hoegh-Guldberg%201999.pdf.
• Anthony, K. R. N., Kline, D. I., Diaz-Pulido, G., Dove, S., and Hoegh-Guldberg, O. (2008). Ocean acidification causes bleaching and productivity loss in coral reef builders. PNAS , 105 (45), 17442-17446. http://dx.doi.org/10.1073/pnas.0804478105 .
• University of California Museum of Paleontology. (2016). Misconceptions about science. In Understanding science . Retrieved from http://undsci.berkeley.edu/teaching/misconceptions.php .
• Hoegh-Guldberg, O. and Smith, G. J. (1989). The effect of sudden changes in temperature, light and salinity on the density and export of zooxanthellae from the reef corals Stylophora pistillata (Esper, 1797) and Seriatopora hystrix (Dana, 1846). J. Exp. Mar. Biol. Ecol. , 129 , 279-303. Retrieved from http://www.reef.edu.au/ohg/res-pic/HG%20papers/HG%20and%20Smith%201989%20BLEACH.pdf .

Additional references:

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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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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.

Variables and Attributes

In science, when a variable is studied, its attribute is recorded. A variable is a characteristic, while an attribute is its state. For example, if eye color is the variable, its attribute might be green, brown, or blue. If height is the variable, its attribute might be 5 m, 2.5 cm, or 1.22 km.

• Earl R. Babbie. The Practice of Social Research , 12th edition. Wadsworth Publishing, 2009.
• What Is a Dependent Variable?
• What Is an Experiment? Definition and Design
• Six Steps of the Scientific Method
• Examples of Independent and Dependent Variables
• How To Design a Science Fair Experiment
• The Role of a Controlled Variable in an Experiment
• Scientific Variable
• What Are the Elements of a Good Hypothesis?
• Dependent Variable vs. Independent Variable: What Is the Difference?
• What Is the Difference Between a Control Variable and Control Group?
• Independent Variable Definition and Examples
• Null Hypothesis Examples
• What Is a Controlled Experiment?
• DRY MIX Experiment Variables Acronym
• Scientific Method Vocabulary Terms
• What Is the Difference Between Hard and Soft Science?

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Dependent & Independent Variables in Science Experiments

by Chloe Campbell Leave a Comment

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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Experimental Design - Independent, Dependent, and Controlled Variables

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Scientific experiments are meant to show cause and effect of a phenomena (relationships in nature).  The “ variables ” are any factor, trait, or condition that can be changed in the experiment and that can have an effect on the outcome of the experiment.

An experiment can have three kinds of variables: i ndependent, dependent, and controlled .

• The independent variable is one single factor that is changed by the scientist followed by observation to watch for changes. It is important that there is just one independent variable, so that results are not confusing.
• The dependent variable is the factor that changes as a result of the change to the independent variable.
• The controlled variables (or constant variables) are factors that the scientist wants to remain constant if the experiment is to show accurate results. To be able to measure results, each of the variables must be able to be measured.

For example, let’s design an experiment with two plants sitting in the sun side by side. The controlled variables (or constants) are that at the beginning of the experiment, the plants are the same size, get the same amount of sunlight, experience the same ambient temperature and are in the same amount and consistency of soil (the weight of the soil and container should be measured before the plants are added). The independent variable is that one plant is getting watered (1 cup of water) every day and one plant is getting watered (1 cup of water) once a week. The dependent variables are the changes in the two plants that the scientist observes over time.

Can you describe the dependent variable that may result from this experiment? After four weeks, the dependent variable may be that one plant is taller, heavier and more developed than the other. These results can be recorded and graphed by measuring and comparing both plants’ height, weight (removing the weight of the soil and container recorded beforehand) and a comparison of observable foliage.

Using What You Learned: Design another experiment using the two plants, but change the independent variable. Can you describe the dependent variable that may result from this new experiment?

Think of another simple experiment and name the independent, dependent, and controlled variables. Use the graphic organizer included in the PDF below to organize your experiment's variables.

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15 Independent and Dependent Variable Examples

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An independent variable (IV) is what is manipulated in a scientific experiment to determine its effect on the dependent variable (DV).

By varying the level of the independent variable and observing associated changes in the dependent variable, a researcher can conclude whether the independent variable affects the dependent variable or not.

This can provide very valuable information when studying just about any subject.

Because the researcher controls the level of the independent variable, it can be determined if the independent variable has a causal effect on the dependent variable.

The term causation is vitally important. Scientists want to know what causes changes in the dependent variable. The only way to do that is to manipulate the independent variable and observe any changes in the dependent variable.

Definition of Independent and Dependent Variables

The independent variable and dependent variable are used in a very specific type of scientific study called the experiment .

Although there are many variations of the experiment, generally speaking, it involves either the presence or absence of the independent variable and the observation of what happens to the dependent variable.

The research participants are randomly assigned to either receive the independent variable (called the treatment condition), or not receive the independent variable (called the control condition).

Other variations of an experiment might include having multiple levels of the independent variable.

If the independent variable affects the dependent variable, then it should be possible to observe changes in the dependent variable based on the presence or absence of the independent variable.  

Of course, there are a lot of issues to consider when conducting an experiment, but these are the basic principles.

These concepts should not be confused with predictor and outcome variables .

Examples of Independent and Dependent Variables

1. gatorade and improved athletic performance.

A sports medicine researcher has been hired by Gatorade to test the effects of its sports drink on athletic performance. The company wants to claim that when an athlete drinks Gatorade, their performance will improve.

If they can back up that claim with hard scientific data, that would be great for sales.

So, the researcher goes to a nearby university and randomly selects both male and female athletes from several sports: track and field, volleyball, basketball, and football. Each athlete will run on a treadmill for one hour while their heart rate is tracked.

All of the athletes are given the exact same amount of liquid to consume 30-minutes before and during their run. Half are given Gatorade, and the other half are given water, but no one knows what they are given because both liquids have been colored.

In this example, the independent variable is Gatorade, and the dependent variable is heart rate.  

2. Chemotherapy and Cancer

A hospital is investigating the effectiveness of a new type of chemotherapy on cancer. The researchers identified 120 patients with relatively similar types of cancerous tumors in both size and stage of progression.

The patients are randomly assigned to one of three groups: one group receives no chemotherapy, one group receives a low dose of chemotherapy, and one group receives a high dose of chemotherapy.

Each group receives chemotherapy treatment three times a week for two months, except for the no-treatment group. At the end of two months, the doctors measure the size of each patient’s tumor.

In this study, despite the ethical issues (remember this is just a hypothetical example), the independent variable is chemotherapy, and the dependent variable is tumor size.

3. Interior Design Color and Eating Rate

A well-known fast-food corporation wants to know if the color of the interior of their restaurants will affect how fast people eat. Of course, they would prefer that consumers enter and exit quickly to increase sales volume and profit.

So, they rent space in a large shopping mall and create three different simulated restaurant interiors of different colors. One room is painted mostly white with red trim and seats; one room is painted mostly white with blue trim and seats; and one room is painted mostly white with off-white trim and seats.

Next, they randomly select shoppers on Saturdays and Sundays to eat for free in one of the three rooms. Each shopper is given a box of the same food and drink items and sent to one of the rooms. The researchers record how much time elapses from the moment they enter the room to the moment they leave.

The independent variable is the color of the room, and the dependent variable is the amount of time spent in the room eating.

4. Hair Color and Attraction

A large multinational cosmetics company wants to know if the color of a woman’s hair affects the level of perceived attractiveness in males. So, they use Photoshop to manipulate the same image of a female by altering the color of her hair: blonde, brunette, red, and brown.

Next, they randomly select university males to enter their testing facilities. Each participant sits in front of a computer screen and responds to questions on a survey. At the end of the survey, the screen shows one of the photos of the female.

At the same time, software on the computer that utilizes the computer’s camera is measuring each male’s pupil dilation. The researchers believe that larger dilation indicates greater perceived attractiveness.

The independent variable is hair color, and the dependent variable is pupil dilation.

5. Mozart and Math

After many claims that listening to Mozart will make you smarter, a group of education specialists decides to put it to the test. So, first, they go to a nearby school in a middle-class neighborhood.

During the first three months of the academic year, they randomly select some 5th-grade classrooms to listen to Mozart during their lessons and exams. Other 5 th grade classrooms will not listen to any music during their lessons and exams.

The researchers then compare the scores of the exams between the two groups of classrooms.

Although there are a lot of obvious limitations to this hypothetical, it is the first step.

The independent variable is Mozart, and the dependent variable is exam scores.

6. Essential Oils and Sleep

A company that specializes in essential oils wants to examine the effects of lavender on sleep quality. They hire a sleep research lab to conduct the study. The researchers at the lab have their usual test volunteers sleep in individual rooms every night for one week.

The conditions of each room are all exactly the same, except that half of the rooms have lavender released into the rooms and half do not. While the study participants are sleeping, their heart rates and amount of time spent in deep sleep are recorded with high-tech equipment.

At the end of the study, the researchers compare the total amount of time spent in deep sleep of the lavender-room participants with the no lavender-room participants.

The independent variable in this sleep study is lavender, and the dependent variable is the total amount of time spent in deep sleep.

7. Teaching Style and Learning

A group of teachers is interested in which teaching method will work best for developing critical thinking skills.

So, they train a group of teachers in three different teaching styles : teacher-centered, where the teacher tells the students all about critical thinking; student-centered, where the students practice critical thinking and receive teacher feedback; and AI-assisted teaching, where the teacher uses a special software program to teach critical thinking.

At the end of three months, all the students take the same test that assesses critical thinking skills. The teachers then compare the scores of each of the three groups of students.

The independent variable is the teaching method, and the dependent variable is performance on the critical thinking test.

8. Concrete Mix and Bridge Strength

A chemicals company has developed three different versions of their concrete mix. Each version contains a different blend of specially developed chemicals. The company wants to know which version is the strongest.

So, they create three bridge molds that are identical in every way. They fill each mold with one of the different concrete mixtures. Next, they test the strength of each bridge by placing progressively more weight on its center until the bridge collapses.

In this study, the independent variable is the concrete mixture, and the dependent variable is the amount of weight at collapse.

9. Recipe and Consumer Preferences

People in the pizza business know that the crust is key. Many companies, large and small, will keep their recipe a top secret. Before rolling out a new type of crust, the company decides to conduct some research on consumer preferences.

The company has prepared three versions of their crust that vary in crunchiness, they are: a little crunchy, very crunchy, and super crunchy. They already have a pool of consumers that fit their customer profile and they often use them for testing.

Each participant sits in a booth and takes a bite of one version of the crust. They then indicate how much they liked it by pressing one of 5 buttons: didn’t like at all, liked, somewhat liked, liked very much, loved it.

The independent variable is the level of crust crunchiness, and the dependent variable is how much it was liked.

10. Protein Supplements and Muscle Mass

A large food company is considering entering the health and nutrition sector. Their R&D food scientists have developed a protein supplement that is designed to help build muscle mass for people that work out regularly.

The company approaches several gyms near its headquarters. They enlist the cooperation of over 120 gym rats that work out 5 days a week. Their muscle mass is measured, and only those with a lower level are selected for the study, leaving a total of 80 study participants.

They randomly assign half of the participants to take the recommended dosage of their supplement every day for three months after each workout. The other half takes the same amount of something that looks the same but actually does nothing to the body.

At the end of three months, the muscle mass of all participants is measured.

The independent variable is the supplement, and the dependent variable is muscle mass.  

11. Air Bags and Skull Fractures

In the early days of airbags , automobile companies conducted a great deal of testing. At first, many people in the industry didn’t think airbags would be effective at all. Fortunately, there was a way to test this theory objectively.

In a representative example: Several crash cars were outfitted with an airbag, and an equal number were not. All crash cars were of the same make, year, and model. Then the crash experts rammed each car into a crash wall at the same speed. Sensors on the crash dummy skulls allowed for a scientific analysis of how much damage a human skull would incur.

The amount of skull damage of dummies in cars with airbags was then compared with those without airbags.

The independent variable was the airbag and the dependent variable was the amount of skull damage.

12. Vitamins and Health

Some people take vitamins every day. A group of health scientists decides to conduct a study to determine if taking vitamins improves health.

They randomly select 1,000 people that are relatively similar in terms of their physical health. The key word here is “similar.”

Because the scientists have an unlimited budget (and because this is a hypothetical example, all of the participants have the same meals delivered to their homes (breakfast, lunch, and dinner), every day for one year.

In addition, the scientists randomly assign half of the participants to take a set of vitamins, supplied by the researchers every day for 1 year. The other half do not take the vitamins.

At the end of one year, the health of all participants is assessed, using blood pressure and cholesterol level as the key measurements.

In this highly unrealistic study, the independent variable is vitamins, and the dependent variable is health, as measured by blood pressure and cholesterol levels.

13. Meditation and Stress

Does practicing meditation reduce stress? If you have ever wondered if this is true or not, then you are in luck because there is a way to know one way or the other.

All we have to do is find 90 people that are similar in age, stress levels, diet and exercise, and as many other factors as we can think of.

Next, we randomly assign each person to either practice meditation every day, three days a week, or not at all. After three months, we measure the stress levels of each person and compare the groups.

How should we measure stress? Well, there are a lot of ways. We could measure blood pressure, or the amount of the stress hormone cortisol in their blood, or by using a paper and pencil measure such as a questionnaire that asks them how much stress they feel.

In this study, the independent variable is meditation and the dependent variable is the amount of stress (however it is measured).

14. Video Games and Aggression

When video games started to become increasingly graphic, it was a huge concern in many countries in the world. Educators, social scientists, and parents were shocked at how graphic games were becoming.

Since then, there have been hundreds of studies conducted by psychologists and other researchers. A lot of those studies used an experimental design that involved males of various ages randomly assigned to play a graphic or non-graphic video game.

Afterward, their level of aggression was measured via a wide range of methods, including direct observations of their behavior, their actions when given the opportunity to be aggressive, or a variety of other measures.

So many studies have used so many different ways of measuring aggression.

In these experimental studies, the independent variable was graphic video games, and the dependent variable was observed level of aggression.

15. Vehicle Exhaust and Cognitive Performance

Car pollution is a concern for a lot of reasons. In addition to being bad for the environment, car exhaust may cause damage to the brain and impair cognitive performance.

One way to examine this possibility would be to conduct an animal study. The research would look something like this: laboratory rats would be raised in three different rooms that varied in the degree of car exhaust circulating in the room: no exhaust, little exhaust, or a lot of exhaust.

After a certain period of time, perhaps several months, the effects on cognitive performance could be measured.

One common way of assessing cognitive performance in laboratory rats is by measuring the amount of time it takes to run a maze successfully. It would also be possible to examine the physical effects of car exhaust on the brain by conducting an autopsy.

In this animal study, the independent variable would be car exhaust and the dependent variable would be amount of time to run a maze.

Read Next: Extraneous Variables Examples

The experiment is an incredibly valuable way to answer scientific questions regarding the cause and effect of certain variables. By manipulating the level of an independent variable and observing corresponding changes in a dependent variable, scientists can gain an understanding of many phenomena.

For example, scientists can learn if graphic video games make people more aggressive, if mediation reduces stress, if Gatorade improves athletic performance, and even if certain medical treatments can cure cancer.

The determination of causality is the key benefit of manipulating the independent variable and them observing changes in the dependent variable. Other research methodologies can reveal factors that are related to the dependent variable or associated with the dependent variable, but only when the independent variable is controlled by the researcher can causality be determined.

Ferguson, C. J. (2010). Blazing Angels or Resident Evil? Can graphic video games be a force for good? Review of General Psychology, 14 (2), 68-81. https://doi.org/10.1037/a0018941

Flannelly, L. T., Flannelly, K. J., & Jankowski, K. R. (2014). Independent, dependent, and other variables in healthcare and chaplaincy research. Journal of Health Care Chaplaincy , 20 (4), 161–170. https://doi.org/10.1080/08854726.2014.959374

Manocha, R., Black, D., Sarris, J., & Stough, C.(2011). A randomized, controlled trial of meditation for work stress, anxiety and depressed mood in full-time workers. Evidence-Based Complementary and Alternative Medicine , vol. 2011, Article ID 960583. https://doi.org/10.1155/2011/960583

Rumrill, P. D., Jr. (2004). Non-manipulation quantitative designs. Work (Reading, Mass.) , 22 (3), 255–260.

Taylor, J. M., & Rowe, B. J. (2012). The “Mozart Effect” and the mathematical connection, Journal of College Reading and Learning, 42 (2), 51-66.  https://doi.org/10.1080/10790195.2012.10850354

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Independent and Dependent Variables: Which Is Which?

General Education

Independent and dependent variables are important for both math and science. If you don't understand what these two variables are and how they differ, you'll struggle to analyze an experiment or plot equations. Fortunately, we make learning these concepts easy!

In this guide, we break down what independent and dependent variables are , give examples of the variables in actual experiments, explain how to properly graph them, provide a quiz to test your skills, and discuss the one other important variable you need to know.

What Is an Independent Variable? What Is a Dependent Variable?

A variable is something you're trying to measure. It can be practically anything, such as objects, amounts of time, feelings, events, or ideas. If you're studying how people feel about different television shows, the variables in that experiment are television shows and feelings. If you're studying how different types of fertilizer affect how tall plants grow, the variables are type of fertilizer and plant height.

There are two key variables in every experiment: the independent variable and the dependent variable.

Independent variable: What the scientist changes or what changes on its own.

Dependent variable: What is being studied/measured.

The independent variable (sometimes known as the manipulated variable) is the variable whose change isn't affected by any other variable in the experiment. Either the scientist has to change the independent variable herself or it changes on its own; nothing else in the experiment affects or changes it. Two examples of common independent variables are age and time. There's nothing you or anything else can do to speed up or slow down time or increase or decrease age. They're independent of everything else.

The dependent variable (sometimes known as the responding variable) is what is being studied and measured in the experiment. It's what changes as a result of the changes to the independent variable. An example of a dependent variable is how tall you are at different ages. The dependent variable (height) depends on the independent variable (age).

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.

It can be a lot easier to understand the differences between these two variables with examples, so let's look at some sample experiments below.

Examples of Independent and Dependent Variables in Experiments

Below are overviews of three experiments, each with their independent and dependent variables identified.

Experiment 1: You want to figure out which brand of microwave popcorn pops the most kernels so you can get the most value for your money. You test different brands of popcorn to see which bag pops the most popcorn kernels.

• Independent Variable: Brand of popcorn bag (It's the independent variable because you are actually deciding the popcorn bag brands)
• Dependent Variable: Number of kernels popped (This is the dependent variable because it's what you measure for each popcorn brand)

Experiment 2 : You want to see which type of fertilizer helps plants grow fastest, so you add a different brand of fertilizer to each plant and see how tall they grow.

• Independent Variable: Type of fertilizer given to the plant
• Dependent Variable: Plant height

Experiment 3: You're interested in how rising sea temperatures impact algae life, so you design an experiment that measures the number of algae in a sample of water taken from a specific ocean site under varying temperatures.

• Independent Variable: Ocean temperature
• Dependent Variable: The number of algae in the sample

For each of the independent variables above, it's clear that they can't be changed by other variables in the experiment. You have to be the one to change the popcorn and fertilizer brands in Experiments 1 and 2, and the ocean temperature in Experiment 3 cannot be significantly changed by other factors. Changes to each of these independent variables cause the dependent variables to change in the experiments.

Where Do You Put Independent and Dependent Variables on Graphs?

Independent and dependent variables always go on the same places in a graph. This makes it easy for you to quickly see which variable is independent and which is dependent when looking at a graph or chart. The independent variable always goes on the x-axis, or the horizontal axis. The dependent variable goes on the y-axis, or vertical axis.

Here's an example:

As you can see, this is a graph showing how the number of hours a student studies affects the score she got on an exam. From the graph, it looks like studying up to six hours helped her raise her score, but as she studied more than that her score dropped slightly.

The amount of time studied is the independent variable, because it's what she changed, so it's on the x-axis. The score she got on the exam is the dependent variable, because it's what changed as a result of the independent variable, and it's on the y-axis. It's common to put the units in parentheses next to the axis titles, which this graph does.

There are different ways to title a graph, but a common way is "[Independent Variable] vs. [Dependent Variable]" like this graph. Using a standard title like that also makes it easy for others to see what your independent and dependent variables are.

Are There Other Important Variables to Know?

Independent and dependent variables are the two most important variables to know and understand when conducting or studying an experiment, but there is one other type of variable that you should be aware of: constant variables.

Constant variables (also known as "constants") are simple to understand: they're what stay the same during the experiment. Most experiments usually only have one independent variable and one dependent variable, but they will all have multiple constant variables.

For example, in Experiment 2 above, some of the constant variables would be the type of plant being grown, the amount of fertilizer each plant is given, the amount of water each plant is given, when each plant is given fertilizer and water, the amount of sunlight the plants receive, the size of the container each plant is grown in, and more. The scientist is changing the type of fertilizer each plant gets which in turn changes how much each plant grows, but every other part of the experiment stays the same.

In experiments, you have to test one independent variable at a time in order to accurately understand how it impacts the dependent variable. Constant variables are important because they ensure that the dependent variable is changing because, and only because, of the independent variable so you can accurately measure the relationship between the dependent and independent variables.

If you didn't have any constant variables, you wouldn't be able to tell if the independent variable was what was really affecting the dependent variable. For example, in the example above, if there were no constants and you used different amounts of water, different types of plants, different amounts of fertilizer and put the plants in windows that got different amounts of sun, you wouldn't be able to say how fertilizer type affected plant growth because there would be so many other factors potentially affecting how the plants grew.

3 Experiments to Help You Understand Independent and Dependent Variables

If you're still having a hard time understanding the relationship between independent and dependent variable, it might help to see them in action. Here are three experiments you can try at home.

Experiment 1: Plant Growth Rates

One simple way to explore independent and dependent variables is to construct a biology experiment with seeds. Try growing some sunflowers and see how different factors affect their growth. For example, say you have ten sunflower seedlings, and you decide to give each a different amount of water each day to see if that affects their growth. The independent variable here would be the amount of water you give the plants, and the dependent variable is how tall the sunflowers grow.

Experiment 2: Chemical Reactions

Explore a wide range of chemical reactions with this chemistry kit . It includes 100+ ideas for experiments—pick one that interests you and analyze what the different variables are in the experiment!

Experiment 3: Simple Machines

Build and test a range of simple and complex machines with this K'nex kit . How does increasing a vehicle's mass affect its velocity? Can you lift more with a fixed or movable pulley? Remember, the independent variable is what you control/change, and the dependent variable is what changes because of that.

Quiz: Test Your Variable Knowledge

Can you identify the independent and dependent variables for each of the four scenarios below? The answers are at the bottom of the guide for you to check your work.

Scenario 1: You buy your dog multiple brands of food to see which one is her favorite.

Scenario 2: Your friends invite you to a party, and you decide to attend, but you're worried that staying out too long will affect how well you do on your geometry test tomorrow morning.

Scenario 3: Your dentist appointment will take 30 minutes from start to finish, but that doesn't include waiting in the lounge before you're called in. The total amount of time you spend in the dentist's office is the amount of time you wait before your appointment, plus the 30 minutes of the actual appointment

Scenario 4: You regularly babysit your little cousin who always throws a tantrum when he's asked to eat his vegetables. Over the course of the week, you ask him to eat vegetables four times.

Summary: Independent vs Dependent Variable

Knowing the independent variable definition and dependent variable definition is key to understanding how experiments work. The independent variable is what you change, and the dependent variable is what changes as a result of that. You can also think of the independent variable as the cause and the dependent variable as the effect.

When graphing these variables, the independent variable should go on the x-axis (the horizontal axis), and the dependent variable goes on the y-axis (vertical axis).

Constant variables are also important to understand. They are what stay the same throughout the experiment so you can accurately measure the impact of the independent variable on the dependent variable.

What's Next?

Independent and dependent variables are commonly taught in high school science classes. Read our guide to learn which science classes high school students should be taking.

Scoring well on standardized tests is an important part of having a strong college application. Check out our guides on the best study tips for the SAT and ACT.

Interested in science? Science Olympiad is a great extracurricular to include on your college applications, and it can help you win big scholarships. Check out our complete guide to winning Science Olympiad competitions.

Quiz Answers

1: Independent: dog food brands; Dependent: how much you dog eats

2: Independent: how long you spend at the party; Dependent: your exam score

3: Independent: Amount of time you spend waiting; Dependent: Total time you're at the dentist (the 30 minutes of appointment time is the constant)

4: Independent: Number of times your cousin is asked to eat vegetables; Dependent: number of tantrums

These recommendations are based solely on our knowledge and experience. If you purchase an item through one of our links, PrepScholar may receive a commission.

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Teaching About Variables in Science

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If you are teaching the scientific method in your classroom, then you should also be teaching about variables! A variable is something that can change or vary for an experiment to be a success. There are three types- an independent variable (sometimes called a manipulated variable), a dependent variable (sometimes referred to as the responding variable), and the controlled variable. Each has an important role to play in experiments.

Understanding the Three Variables

Often times students will mix up the three variables. It takes a lot of practice to help them – which is where the experiments come in.

An independent variable asks the question, “Which variable are you testing?” It is also the variable that changes or varies in the experiment. It is part of the research question and is intentionally changed.

A dependent variable asks the question, “What will the results measure?” It depends on the independent variable and is part of the results. It is the factor or condition that might be affected. It’s what you’re measuring.

The controlled variable asks the question, “What things will you make sure will stay the same during the experiment?” All of these variables do not change and are kept the same the entire time throughout the experiment.

When we control variables, we are able to draw conclusions between the independent and dependent variables without having skewed results.

Teaching About Variables

One of my favorite activities to do that helps to teach about the three different variables is the Paper Towels Lab. I group students up and provide each group with a roll of a generic brand of paper towels and a brand name roll of paper towels. Then I pose the question, “ Will a brand name paper towel absorb more water than a generic paper towel?”

I also provide each group with 250 mL of water, a graduated cylinder, and a tin pan.

I have each group measure out a piece of paper towel that is the same perimeter. We discuss how we don’t want the size of the paper towel to affect the results. This is part of the controlled variables.

Then we all pour 250 mL of water into our tin pans and dip one paper towel for 30 seconds. We count together. Again, we discuss that these are the controlled variables because we are going to keep the amount of water the same for both types of paper towels and the amount of time.

After 30 seconds, we remove the paper towel from the tin and hold it up above our tin and allow it to drip. We all hold it with one hand and count 30 seconds again.

We place our paper towel to the side and then take the water in the tin pan and carefully pour it into the graduated cylinder to measure it. Then we subtract that number from our original number (250 mL) to discover the difference. The difference is how much water that particular paper towel could hold.

We then repeat the experiment with the other brand of paper towels. We do everything the exact same way.

We also discuss the importance of repeated trials. We repeat the test 2 more times for each type of paper towel to get an average.

What we found was indeed the name brand paper towel did hold more water than the generic brand.

The Results of our Paper Towel Lab

Once the lab was over, we discussed again the three variables. The independent variable was the type of paper towel because it was what we were testing. We wanted to know which would hold more water. The dependent variable was the amount of water being absorbed. We know this because it was what we were measuring. It completely depended on the independent variable. The controlled variables were the same size paper towels, the amount of time they were submerged in water, the amount of time they dripped, the same amount of water each time, and so on.

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After completing this lab, have your students practice identifying the various types of variables using this freebie!

Students read the science lab scenarios and then highlight the independent variable, the dependent variable, and the controlled variables in a different color. Click here to download it immediately FREE!

Are you looking for other scientific method ideas? Check out my Scientific Method Unit , or my blog post about Starting Fresh Teaching the Scientific Method.

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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

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WRITTEN BY: Ms Joy – SCIENCE TEACHER

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Variables in Research

In the realm of research, particularly in mathematics and the sciences understanding the concept of the variables is fundamental. The Variables are integral to the formulation of hypotheses the design of the experiments and interpretation of data. They serve as the building blocks for the mathematical models and statistical analyses making it possible to describe, analyze and predict phenomena.

This article aims to provide a comprehensive overview of the variables in the research explaining their significance, types and roles. By the end of this article, students and researchers will have a clearer understanding of how to identify, use and interpret variables in their research projects.

Table of Content

What are Variables?

Types of variables, independent variables, dependent variables, control variables, extraneous variables, moderator variables, mediator variables.

Variables are elements that can change or vary within the experiment or study. They can represent different types of data such as numerical values, categories or even qualitative attributes. In mathematical terms, variables are symbols that can assume different values.

Various types of variables are:

Definition: Variables that are manipulated or controlled in an experiment to observe their effect on other variables.

Example: In a study examining the effect of study time on the test scores the amount of the study time is the independent variable.

Definition: Variables that are measured or observed in response to the changes in the independent variable.

Example: In the same study the test scores are the dependent variable.

Definition: Variables that are kept constant to ensure that the results are due to the manipulation of the independent variable.

Example: The study environment could be a control variable in the study on the study time and test scores.

Definition: Variables that are not intentionally studied but could affect the outcome of the experiment.

Example: The amount of the sleep students get before the test could be an extraneous variable.

Definition: V ariables that influence the strength or direction of the relationship between independent and dependent variables.

Example: The difficulty of the test could be a moderator variable affecting the relationship between the study time and test scores.

Definition: Variables that explain the process through which the independent variable affects the dependent variable.

Example: The level of the understanding of the material could be a mediator variable in the study on study time and test scores.

Role of Variables in Research

Variables are crucial in research for the several reasons:

• Formulating Hypotheses: Variables help in defining and formulating hypotheses in which are essential for the conducting experiments and studies.
• Designing Experiments: Variables determine the structure and design of the experiments guiding the procedures for the data collection and analysis.
• Analyzing Data: Understanding the relationships between the variables is key to the analyzing data and drawing meaningful conclusions from the research.
• Predicting Outcomes: Variables are used in mathematical models to the predict outcomes and make informed decisions based on the data.

Example: Using Variables in a Mathematical Research Study

Let’s consider a study investigating the relationship between the number of the hours spent practicing a mathematical problem and the performance on the test.

• Independent Variable: Number of hours spent practicing.
• Dependent Variable: Test performance (score).
• Control Variable: Type of the mathematical problems practiced.
• Extraneous Variable: Prior knowledge of the subject.
• Moderator Variable: Complexity of the problems.
• Mediator Variable: Confidence level of the student.

Step-by-Step Example

Formulating the Hypothesis: “Increasing the number of hours spent practicing mathematical problems will improve the test performance.”

• Designing Experiment: Students are divided into groups based on the different practice hours (1 hour, 2 hours, 3 hours).
• Data Collection: Test scores are collected after the practice sessions.
• Data Analysis: The relationship between the practice hours and test scores is analyzed using the statistical methods.
• Conclusion: The findings are used to the draw conclusions about the impact of the practice on test performance.

Visualizing Data

Visualizing data helps in understanding the relationships between the variables. Here are some common methods:

• Scatter Plots: To visualize the relationship between the two continuous variables.
• Bar Charts: To compare the means of the different groups.
• Histograms: To show the distribution of the single variable.

Questions on Variables in Research

Question 1: In a study examining the effect of the sleep on the academic performance identify the independent, dependent and control variables.

Independent Variable: Amount of sleep. Dependent Variable: Academic performance (grades). Control Variable: Study environment, type of the academic tasks.

Question 2: Explain how an extraneous variable can affect the outcome of an experiment.

An extraneous variable such as the amount of the caffeine consumed could affect the academic performance of the students in a study examining the effect of sleep on the academic performance. If not controlled it could confound the results by the influencing the dependent variable independently of the independent variable.

Question 3: Describe how you would control for extraneous variables in a study.

To control for the extraneous variables researchers can use the random assignment ensure consistent conditions or include the extraneous variables in the statistical analysis to the account for their potential impact.

Practice Questions on Variables in Research

Q1: How can you identify the independent variable in a given research study?

Q2: What steps can you take to ensure that control variables are effectively managed in an experiment?

Q3: How does the presence of extraneous variables impact the validity of research findings?

Q4: In what ways can a moderator variable affect the relationship between independent and dependent variables?

Q5: What are some common methods for visualizing the relationship between independent and dependent variables?

Q6: How can you determine if a variable should be classified as a mediator in your research?

Q7: What are the key differences between categorical and continuous variables, and how do they influence data analysis?

Q8: How do you formulate a hypothesis involving multiple variables in a complex study?

Q9: What strategies can be employed to reduce the impact of extraneous variables in field research?

Q10: How can statistical methods be used to account for control variables in the analysis of research data?

Variables are the cornerstone of the research in mathematics and other sciences. They allow researchers to the formulate hypotheses, design experiments analyze data and draw meaningful conclusions. By understanding and effectively managing different types of the variables researchers can enhance the validity and reliability of their studies.

Concept of variable and Raw data Dependent and Independent variable

FAQs on Variables in Research

What is an independent variable.

An independent variable is the variable that is manipulated in an experiment to the observe its effect on the dependent variable.

What is a dependent variable?

A dependent variable is the variable that is measured or observed in the response to the changes in the independent variable.

Why are control variables important?

Control variables are important because they help ensure that the results of an experiment are due to the manipulation of the independent variable and not other factors.

What is the difference between moderator and mediator variables?

Moderator variables influence the strength or direction of the relationship between the independent and dependent variables while mediator variables explain the process through which the independent variable affects the dependent variable.

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Abstract: In this paper, we prove the compact embedding from the variable-order Sobolev space $W^{s(x,y),p(x,y)}_0 (\Omega)$ to the Nakano space $L^{q(x)}(\Omega)$ with a critical exponent $q(x)$ satisfying some conditions. It is noteworthy that the embedding can be compact even when $q(x)$ reaches the critical Sobolev exponent $p_s^*(x)$. As an application, we obtain a nontrivial solution of the Choquard equation \begin{equation*} \displaystyle (-\Delta)_{p(\cdot,\cdot)}^{s(\cdot,\cdot)}u+|u|^{p(x,x)-2}u=\left(\int_{\Omega}\frac{|u(y)|^{r(y)}}{|x-y|^{\frac{\alpha(x)+\alpha(y)}{2}}}dy\right) |u(x)|^{r(x)-2}u(x)\quad\text{in $\Omega$} \end{equation*} with variable upper critical exponent in the sense of Hardy-Littlewood-Sobolev inequality under an appropriate boundary condition.

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• Fox, Glen P.
• Kelly, Alison M.

The size and complexity of datasets resulting from comparative research experiments in the agricultural domain is constantly increasing. Often the number of variables measured in an experiment exceeds the number of experimental units composing the experiment. When there is a necessity to model the covariance relationships that exist between variables in these experiments, estimation difficulties can arise due to the resulting covariance structure being of reduced rank. A statistical method, based in a linear mixed model framework, is presented for the analysis of designed experiments where datasets are characterised by a greater number of variables than experimental units, and for which the modelling of complex covariance structures between variables is desired. Aided by a clustering algorithm, the method enables the estimation of covariance through the introduction of covariance clusters as random effects into the modelling framework, providing an extension of the traditional variance components model for building covariance structures. The method was applied to a multi-phase mass spectrometry-based proteomics experiment, with the aim of exploring changes in the proteome of barley grain over time during the malting process. The modelling approach provides a new linear mixed model-based method for the estimation of covariance structures between variables measured from designed experiments, when there are a small number of experimental units, or observations, informing covariance parameter estimates.

• k-Means clustering;
• Linear mixed model;
• Mass spectrometry;
• Multi-phase design;

Demarketization and Corruption in China: Evidence from a Quasi-Experiment

• Research Article
• Published: 08 August 2024

Cite this article

• Zhipeng Ye   ORCID: orcid.org/0000-0002-6930-7647 1 &
• Sunny L. Yang   ORCID: orcid.org/0000-0003-1430-6679 2  

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Although corruption persists in the process of marketization in transitional economies, there is still a lack of sufficient evidence on the exact causal effects and mechanisms of demarketization on corruption. As an external shock, the Global Financial Crisis presents an opportunity for a quasi-experiment that allows for the differentiation of declining levels of marketization between China’s developed coastal areas and other areas. This article aims to empirically examine the relationship between demarketization and provincial corruption levels in China, combining an instrumental variable method with a synthetic control approach. The study reveals that foreign direct investment outflow leads to a substantial decline in corruption levels by decreasing rent-seeking opportunities. These findings provide robust evidence to support the negative causal relationship between demarketization and corruption in transitional economies, where marketization alone cannot effectively curb corruption in the presence of a dual-track economy.

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This research was supported by the Fundamental Research Funds for the Central Universities(2021ECNU-HWCBFBLW005 & 2022QKT005)and the National Social Science Foundation of China (22CZZ045).

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Center for Chinese Public Administration Research & School of Government, Sun Yat-sen University, No. 135, Xingang Xi Road, Guangzhou, 510275, China

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Ye, Z., Yang, S.L. Demarketization and Corruption in China: Evidence from a Quasi-Experiment. J OF CHIN POLIT SCI (2024). https://doi.org/10.1007/s11366-024-09895-1

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Accepted : 20 July 2024

Published : 08 August 2024

DOI : https://doi.org/10.1007/s11366-024-09895-1

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