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• Independent vs. Dependent Variables | Definition & Examples

Independent vs. Dependent Variables | Definition & Examples

Published on February 3, 2022 by Pritha Bhandari . Revised on June 22, 2023.

In research, variables are any characteristics that can take on different values, such as height, age, temperature, or test scores.

Researchers often manipulate or measure independent and dependent variables in studies to test cause-and-effect relationships.

• The independent variable is the cause. Its value is independent of other variables in your study.
• The dependent variable is the effect. Its value depends on changes in the independent variable.

Your independent variable is the temperature of the room. You vary the room temperature by making it cooler for half the participants, and warmer for the other half.

Table of contents

What is an independent variable, types of independent variables, what is a dependent variable, identifying independent vs. dependent variables, independent and dependent variables in research, visualizing independent and dependent variables, other interesting articles, frequently asked questions about independent and dependent variables.

An independent variable is the variable you manipulate or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

Independent variables are also called:

• Explanatory variables (they explain an event or outcome)
• Predictor variables (they can be used to predict the value of a dependent variable)
• Right-hand-side variables (they appear on the right-hand side of a regression equation).

These terms are especially used in statistics , where you estimate the extent to which an independent variable change can explain or predict changes in the dependent variable.

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There are two main types of independent variables.

• Experimental independent variables can be directly manipulated by researchers.
• Subject variables cannot be manipulated by researchers, but they can be used to group research subjects categorically.

Experimental variables

In experiments, you manipulate independent variables directly to see how they affect your dependent variable. The independent variable is usually applied at different levels to see how the outcomes differ.

You can apply just two levels in order to find out if an independent variable has an effect at all.

You can also apply multiple levels to find out how the independent variable affects the dependent variable.

You have three independent variable levels, and each group gets a different level of treatment.

You randomly assign your patients to one of the three groups:

• A low-dose experimental group
• A high-dose experimental group
• A placebo group (to research a possible placebo effect )

A true experiment requires you to randomly assign different levels of an independent variable to your participants.

Random assignment helps you control participant characteristics, so that they don’t affect your experimental results. This helps you to have confidence that your dependent variable results come solely from the independent variable manipulation.

Subject variables

Subject variables are characteristics that vary across participants, and they can’t be manipulated by researchers. For example, gender identity, ethnicity, race, income, and education are all important subject variables that social researchers treat as independent variables.

It’s not possible to randomly assign these to participants, since these are characteristics of already existing groups. Instead, you can create a research design where you compare the outcomes of groups of participants with characteristics. This is a quasi-experimental design because there’s no random assignment. Note that any research methods that use non-random assignment are at risk for research biases like selection bias and sampling bias .

Your independent variable is a subject variable, namely the gender identity of the participants. You have three groups: men, women and other.

Your dependent variable is the brain activity response to hearing infant cries. You record brain activity with fMRI scans when participants hear infant cries without their awareness.

A dependent variable is the variable that changes as a result of the independent variable manipulation. It’s the outcome you’re interested in measuring, and it “depends” on your independent variable.

In statistics , dependent variables are also called:

• Response variables (they respond to a change in another variable)
• Outcome variables (they represent the outcome you want to measure)
• Left-hand-side variables (they appear on the left-hand side of a regression equation)

The dependent variable is what you record after you’ve manipulated the independent variable. You use this measurement data to check whether and to what extent your independent variable influences the dependent variable by conducting statistical analyses.

Based on your findings, you can estimate the degree to which your independent variable variation drives changes in your dependent variable. You can also predict how much your dependent variable will change as a result of variation in the independent variable.

Distinguishing between independent and dependent variables can be tricky when designing a complex study or reading an academic research paper .

A dependent variable from one study can be the independent variable in another study, so it’s important to pay attention to research design .

Here are some tips for identifying each variable type.

Recognizing independent variables

Use this list of questions to check whether you’re dealing with an independent variable:

• Is the variable manipulated, controlled, or used as a subject grouping method by the researcher?
• Does this variable come before the other variable in time?
• Is the researcher trying to understand whether or how this variable affects another variable?

Recognizing dependent variables

Check whether you’re dealing with a dependent variable:

• Is this variable measured as an outcome of the study?
• Is this variable dependent on another variable in the study?
• Does this variable get measured only after other variables are altered?

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Independent and dependent variables are generally used in experimental and quasi-experimental research.

Here are some examples of research questions and corresponding independent and dependent variables.

For experimental data, you analyze your results by generating descriptive statistics and visualizing your findings. Then, you select an appropriate statistical test to test your hypothesis .

The type of test is determined by:

• your variable types
• level of measurement
• number of independent variable levels.

You’ll often use t tests or ANOVAs to analyze your data and answer your research questions.

In quantitative research , it’s good practice to use charts or graphs to visualize the results of studies. Generally, the independent variable goes on the x -axis (horizontal) and the dependent variable on the y -axis (vertical).

The type of visualization you use depends on the variable types in your research questions:

• A bar chart is ideal when you have a categorical independent variable.
• A scatter plot or line graph is best when your independent and dependent variables are both quantitative.

To inspect your data, you place your independent variable of treatment level on the x -axis and the dependent variable of blood pressure on the y -axis.

You plot bars for each treatment group before and after the treatment to show the difference in blood pressure.

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

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it “depends” on your independent variable.

In statistics, dependent variables are also called:

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment .

• The type of soda – diet or regular – is the independent variable .
• The level of blood sugar that you measure is the dependent variable – it changes depending on the type of soda.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

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What Is An Independent Variable?

The history of variables, independent variables, a final word.

An independent variable is one of the two types of variables used in a scientific experiment. The independent variable is the variable that can be controlled and changed; the dependent variable is directly affected by the change in the independent variable. 

If you think back to the last science class you took, you probably remember a lot of discussion surrounding variables. In fact, this concept is widespread and applied to many different areas of life, but it has the same fundamental meaning. The weather can be “variable”, meaning that it changes quite often, and the same can be said of personalities and moods. By introducing a new “variable” into a situation, such as inviting your new in-laws over for Christmas, you are expecting the outcome to be different than if they were not in attendance.

Although you might not think of these small, daily occurrences as “experiments”, every decision in life can be compared to a scientific study! However, what you may not remember from your science class is the difference between certain variable types. This article will dive into these specifics a bit deeper, particularly in terms of independent variables .

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In the human history of logic and reasoning, there have been many critical turning points, but one of the most fundamental concepts—the variable—has its origins in 7th century India, specifically with a mathematician named Brahmagupta. Not only was he the first mathematician to outline rules for the use of “zero”, but also developed the first rudimentary system to analyze unknowns. When designing and expressing algebraic equations, he used different colored patches to label different known and unknown quantities.

Nearly 1,000 years later, in the west, a similar concept of labeling unknown and known quantities with letters was introduced. In his equations, he utilized consonants for known quantities, and vowels for unknown quantities. Less than a century later, Rene Descartes instead chose to use a, b and c for known quantities, and x, y and z for unknown quantities. To this day, this is the standard system that remains in use across most of the sciences, including mathematics.

Two hundred years later, the idea of infinitesimal calculus was developed, which led to the development of a “function”, in which an infinitesimal variation of a variable quantity causes a corresponding variation in another quantity, making the latter of a function of the former. Without going beyond the scope of this article, this deeper definition of a variable has led to incredible modern advancements in engineering, economics and mathematics, among many others.

Variables have proven to be invaluable for the calculation and theorization of complex ideas and computations across a multitude of fields. but in the realm of scientific experiments, variables take on a slightly different (and simpler) role.

Also Read: What Is Endogeneity? What Is An Exogenous Variable?

As mentioned above, independent and dependent variables are the two key components of an experiment. Quite simply, the independent variable is the state, condition or experimental element that is controlled and manipulated by the experimenter. The dependent variable is what an experimenter is attempting to test, learn about or measure, and will be “dependent” on the independent variable.

This is similar to the mathematical concept of variables, in that an independent variable is a known quantity, and a dependent variable is an unknown quantity. In most scientific experiments, there should only be a single independent variable, as you are attempting to measure the change of other variables in relation to the controlled manipulation of the independent variable. If you change two variables, for example, then it becomes difficult, if not impossible, to determine the exact cause of the variation in the dependent variable.

Understanding Independent Variable With Example

To make this even easier to understand, let’s take a look at an example. Imagine that you’re conducting an experiment in which you want to see what is the best watering pattern for a particular type of plant. You line up three identical styrofoam cups full of the same quantity, quality and density of soil. You then plant three seeds of the same plant variety in each cup. The first cup receives 2 ounces of water once a day, the second cup receives 2 ounces of water every other day, and the third cup receives 2 ounces of water every third day.

In this example, there is only one independent variable—the watering regularity. All of the other potential variables are kept consistent and unchanged, such as the type of plant, the quality of the soil and even the amount of water administered each day. These represent the third type of variable present in any experiment—the controlled variables. If any additional controlled variables were changing, it would be impossible to definitively determine the connection between the independent and dependent variables.

After 4-6 weeks of the experiment, one could measure the amount of growth in each newly sprouted plant; these measurements are the dependent variables, as they are dependent on the amount of water each plant receives (the independent variable).

Also Read: What Is A Controlled Experiment? Aren’t All Experiments Controlled?

This may seem like a simple concept, but it underpins all scientific inquiry, so it’s very important to understand. It is also applicable in your own life every single day. For example, if you’re a scientifically minded person and are unhappy with the direction your life is going, try to change one thing in a concentrated way (i.e., getting a new job, finding/leaving a partner, changing a daily habit etc.). This is your independent variable. After a set amount of time (days, weeks, months), take stock of what has changed since making the change. What you identify as having changed (either good or bad) is your dependent variable!

Changing everything at the exact same time, such as simultaneously leaving a job, ending a relationship and moving to a new city, will make it difficult (if not impossible) to identify which of those changes had the most notable and measurable effect. Obviously, life is unpredictable and some variables cannot be controlled, but thinking about variables and causation in your daily decisions can help you take a more logical and informed path!

• What are Variables? - Science Buddies.
• Rosenthal, A. (1951, February). The History of Calculus. The American Mathematical Monthly. Informa UK Limited.
• Tang, X., Coffey, J. E., Elby, A., & Levin, D. M. (2009, October 7). The scientific method and scientific inquiry: Tensions in teaching and learning. Science Education. Wiley.

John Staughton is a traveling writer, editor, publisher and photographer who earned his English and Integrative Biology degrees from the University of Illinois. He is the co-founder of a literary journal, Sheriff Nottingham, and the Content Director for Stain’d Arts, an arts nonprofit based in Denver. On a perpetual journey towards the idea of home, he uses words to educate, inspire, uplift and evolve.

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What Are Dependent, Independent & Controlled Variables?

What Is a Responding Variable in Science Projects?

Say you're in lab, and your teacher asks you to design an experiment. The experiment must test how plants grow in response to different colored light. How would you begin? What are you changing? What are you keeping the same? What are you measuring?

These parameters of what you would change and what you would keep the same are called variables. Take a look at how all of these parameters in an experiment are defined, as independent, dependent and controlled variables.

What Is a Variable?

A variable is any quantity that you are able to measure in some way. This could be temperature, height, age, etc. Basically, a variable is anything that contributes to the outcome or result of your experiment in any way.

In an experiment there are multiple kinds of variables: independent, dependent and controlled variables.

What Is an Independent Variable?

An independent variable is the variable the experimenter controls. Basically, it is the component you choose to change in an experiment. This variable is not dependent on any other variables.

For example, in the plant growth experiment, the independent variable is the light color. The light color is not affected by anything. You will choose different light colors like green, red, yellow, etc. You are not measuring the light.

What Is a Dependent Variable?

A dependent variable is the measurement that changes in response to what you changed in the experiment. This variable is dependent on other variables; hence the name! For example, in the plant growth experiment, the dependent variable would be plant growth.

You could measure this by measuring how much the plant grows every two days. You could also measure it by measuring the rate of photosynthesis. Either of these measurements are dependent upon the kind of light you give the plant.

What Are Controlled Variables?

A control variable in science is any other parameter affecting your experiment that you try to keep the same across all conditions.

For example, one control variable in the plant growth experiment could be temperature. You would not want to have one plant growing in green light with a temperature of 20°C while another plant grows in red light with a temperature of 27°C.

You want to measure only the effect of light, not temperature. For this reason you would want to keep the temperature the same across all of your plants. In other words, you would want to control the temperature.

Another example is the amount of water you give the plant. If one plant receives twice the amount of water as another plant, there would be no way for you to know that the reason those plants grew the way they did is due only to the light color their received.

The observed effect could also be due in part to the amount of water they got. A control variable in science experiments is what allows you to compare other things that may be contributing to a result because you have kept other important things the same across all of your subjects.

Graphing Your Experiment

When graphing the results of your experiment, it is important to remember which variable goes on which axis.

The independent variable is graphed on the x-axis . The dependent variable , which changes in response to the independent variable, is graphed on the y-axis . Controlled variables are usually not graphed because they should not change. They could, however, be graphed as a verification that other conditions are not changing.

For example, after graphing the growth as compared to light, you could also look at how the temperature varied across different conditions. If you notice that it did vary quite a bit, you may need to go back and look at your experimental setup: How could you improve the experiment so that all plants are exposed to as similar an environment as possible (aside from the light color)?

How to Remember Which is Which

In order to try and remember which is the dependent variable and which is the independent variable, try putting them into a sentence which uses "causes a change in."

Here's an example. Saying, "light color causes a change in plant growth," is possible. This shows us that the independent variable affects the dependent variable. The inverse, however, is not true. "Plant growth causes a change in light color," is not possible. This way you know which is the independent variable and which is the dependent variable!

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• NCES Kids: What are Independent and Dependent Variables?
• Khan Academy: Dependent and independent variables review (article)

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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

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Difference Between Independent and Dependent Variables

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

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

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

How to Tell the Independent and Dependent Variable Apart

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

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

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

Independent Variable

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

Dependent Variable

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

Examples of Independent and Dependent Variables

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

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

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

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

Graphing Independent and Dependent Variables With DRYMIX

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

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

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

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

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• Independent vs Dependent Variables | Definition & Examples

Independent vs Dependent Variables | Definition & Examples

Published on 4 May 2022 by Pritha Bhandari . Revised on 17 October 2022.

In research, variables are any characteristics that can take on different values, such as height, age, temperature, or test scores.

Researchers often manipulate or measure independent and dependent variables in studies to test cause-and-effect relationships.

• The independent variable is the cause. Its value is independent of other variables in your study.
• The dependent variable is the effect. Its value depends on changes in the independent variable.

Your independent variable is the temperature of the room. You vary the room temperature by making it cooler for half the participants, and warmer for the other half.

Table of contents

What is an independent variable, types of independent variables, what is a dependent variable, identifying independent vs dependent variables, independent and dependent variables in research, visualising independent and dependent variables, frequently asked questions about independent and dependent variables.

An independent variable is the variable you manipulate or vary in an experimental study to explore its effects. It’s called ‘independent’ because it’s not influenced by any other variables in the study.

Independent variables are also called:

• Explanatory variables (they explain an event or outcome)
• Predictor variables (they can be used to predict the value of a dependent variable)
• Right-hand-side variables (they appear on the right-hand side of a regression equation).

These terms are especially used in statistics , where you estimate the extent to which an independent variable change can explain or predict changes in the dependent variable.

Prevent plagiarism, run a free check.

There are two main types of independent variables.

• Experimental independent variables can be directly manipulated by researchers.
• Subject variables cannot be manipulated by researchers, but they can be used to group research subjects categorically.

Experimental variables

In experiments, you manipulate independent variables directly to see how they affect your dependent variable. The independent variable is usually applied at different levels to see how the outcomes differ.

You can apply just two levels in order to find out if an independent variable has an effect at all.

You can also apply multiple levels to find out how the independent variable affects the dependent variable.

You have three independent variable levels, and each group gets a different level of treatment.

You randomly assign your patients to one of the three groups:

• A low-dose experimental group
• A high-dose experimental group
• A placebo group

A true experiment requires you to randomly assign different levels of an independent variable to your participants.

Random assignment helps you control participant characteristics, so that they don’t affect your experimental results. This helps you to have confidence that your dependent variable results come solely from the independent variable manipulation.

Subject variables

Subject variables are characteristics that vary across participants, and they can’t be manipulated by researchers. For example, gender identity, ethnicity, race, income, and education are all important subject variables that social researchers treat as independent variables.

It’s not possible to randomly assign these to participants, since these are characteristics of already existing groups. Instead, you can create a research design where you compare the outcomes of groups of participants with characteristics. This is a quasi-experimental design because there’s no random assignment.

Your independent variable is a subject variable, namely the gender identity of the participants. You have three groups: men, women, and other.

Your dependent variable is the brain activity response to hearing infant cries. You record brain activity with fMRI scans when participants hear infant cries without their awareness.

A dependent variable is the variable that changes as a result of the independent variable manipulation. It’s the outcome you’re interested in measuring, and it ‘depends’ on your independent variable.

In statistics , dependent variables are also called:

• Response variables (they respond to a change in another variable)
• Outcome variables (they represent the outcome you want to measure)
• Left-hand-side variables (they appear on the left-hand side of a regression equation)

The dependent variable is what you record after you’ve manipulated the independent variable. You use this measurement data to check whether and to what extent your independent variable influences the dependent variable by conducting statistical analyses.

Based on your findings, you can estimate the degree to which your independent variable variation drives changes in your dependent variable. You can also predict how much your dependent variable will change as a result of variation in the independent variable.

Distinguishing between independent and dependent variables can be tricky when designing a complex study or reading an academic paper.

A dependent variable from one study can be the independent variable in another study, so it’s important to pay attention to research design.

Here are some tips for identifying each variable type.

Recognising independent variables

Use this list of questions to check whether you’re dealing with an independent variable:

• Is the variable manipulated, controlled, or used as a subject grouping method by the researcher?
• Does this variable come before the other variable in time?
• Is the researcher trying to understand whether or how this variable affects another variable?

Recognising dependent variables

Check whether you’re dealing with a dependent variable:

• Is this variable measured as an outcome of the study?
• Is this variable dependent on another variable in the study?
• Does this variable get measured only after other variables are altered?

Independent and dependent variables are generally used in experimental and quasi-experimental research.

Here are some examples of research questions and corresponding independent and dependent variables.

For experimental data, you analyse your results by generating descriptive statistics and visualising your findings. Then, you select an appropriate statistical test to test your hypothesis .

The type of test is determined by:

• Your variable types
• Level of measurement
• Number of independent variable levels

You’ll often use t tests or ANOVAs to analyse your data and answer your research questions.

In quantitative research , it’s good practice to use charts or graphs to visualise the results of studies. Generally, the independent variable goes on the x -axis (horizontal) and the dependent variable on the y -axis (vertical).

The type of visualisation you use depends on the variable types in your research questions:

• A bar chart is ideal when you have a categorical independent variable.
• A scatterplot or line graph is best when your independent and dependent variables are both quantitative.

To inspect your data, you place your independent variable of treatment level on the x -axis and the dependent variable of blood pressure on the y -axis.

You plot bars for each treatment group before and after the treatment to show the difference in blood pressure.

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called ‘independent’ because it’s not influenced by any other variables in the study.

• Right-hand-side variables (they appear on the right-hand side of a regression equation)

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it ‘depends’ on your independent variable.

In statistics, dependent variables are also called:

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

You want to find out how blood sugar levels are affected by drinking diet cola and regular cola, so you conduct an experiment .

• The type of cola – diet or regular – is the independent variable .
• The level of blood sugar that you measure is the dependent variable – it changes depending on the type of cola.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both.

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Independent Variables (Definition + 43 Examples)

Have you ever wondered how scientists make discoveries and how researchers come to understand the world around us? A crucial tool in their kit is the concept of the independent variable, which helps them delve into the mysteries of science and everyday life.

An independent variable is a condition or factor that researchers manipulate to observe its effect on another variable, known as the dependent variable. In simpler terms, it’s like adjusting the dials and watching what happens! By changing the independent variable, scientists can see if and how it causes changes in what they are measuring or observing, helping them make connections and draw conclusions.

In this article, we’ll explore the fascinating world of independent variables, journey through their history, examine theories, and look at a variety of examples from different fields.

History of the Independent Variable

Once upon a time, in a world thirsty for understanding, people observed the stars, the seas, and everything in between, seeking to unlock the mysteries of the universe.

The story of the independent variable begins with a quest for knowledge, a journey taken by thinkers and tinkerers who wanted to explain the wonders and strangeness of the world.

Origins of the Concept

The seeds of the idea of independent variables were sown by Sir Francis Galton , an English polymath, in the 19th century. Galton wore many hats—he was a psychologist, anthropologist, meteorologist, and a statistician!

It was his diverse interests that led him to explore the relationships between different factors and their effects. Galton was curious—how did one thing lead to another, and what could be learned from these connections?

As Galton delved into the world of statistical theories , the concept of independent variables started taking shape.

He was interested in understanding how characteristics, like height and intelligence, were passed down through generations.

Galton’s work laid the foundation for later thinkers to refine and expand the concept, turning it into an invaluable tool for scientific research.

Evolution over Time

After Galton’s pioneering work, the concept of the independent variable continued to evolve and grow. Scientists and researchers from various fields adopted and adapted it, finding new ways to use it to make sense of the world.

They discovered that by manipulating one factor (the independent variable), they could observe changes in another (the dependent variable), leading to groundbreaking insights and discoveries.

Through the years, the independent variable became a cornerstone in experimental design . Researchers in fields like physics, biology, psychology, and sociology used it to test hypotheses, develop theories, and uncover the laws that govern our universe.

The idea that originated from Galton’s curiosity had bloomed into a universal key, unlocking doors to knowledge across disciplines.

Importance in Scientific Research

Today, the independent variable stands tall as a pillar of scientific research. It helps scientists and researchers ask critical questions, test their ideas, and find answers. Without independent variables, we wouldn’t have many of the advancements and understandings that we take for granted today.

The independent variable plays a starring role in experiments, helping us learn about everything from the smallest particles to the vastness of space. It helps researchers create vaccines, understand social behaviors, explore ecological systems, and even develop new technologies.

In the upcoming sections, we’ll dive deeper into what independent variables are, how they work, and how they’re used in various fields.

Together, we’ll uncover the magic of this scientific concept and see how it continues to shape our understanding of the world around us.

What is an Independent Variable?

Embarking on the captivating journey of scientific exploration requires us to grasp the essential terms and ideas. It's akin to a treasure hunter mastering the use of a map and compass.

In our adventure through the realm of independent variables, we’ll delve deeper into some fundamental concepts and definitions to help us navigate this exciting world.

Variables in Research

In the grand tapestry of research, variables are the gems that researchers seek. They’re elements, characteristics, or behaviors that can shift or vary in different circumstances.

Picture them as the myriad of ingredients in a chef’s kitchen—each variable can be adjusted or modified to create a myriad of dishes, each with a unique flavor!

Understanding variables is essential as they form the core of every scientific experiment and observational study.

Types of Variables

Independent Variable The star of our story, the independent variable, is the one that researchers change or control to study its effects. It’s like a chef experimenting with different spices to see how each one alters the taste of the soup. The independent variable is the catalyst, the initial spark that sets the wheels of research in motion.

Dependent Variable The dependent variable is the outcome we observe and measure . It’s the altered flavor of the soup that results from the chef’s culinary experiments. This variable depends on the changes made to the independent variable, hence the name!

Observing how the dependent variable reacts to changes helps scientists draw conclusions and make discoveries.

Control Variable Control variables are the unsung heroes of scientific research. They’re the constants, the elements that researchers keep the same to ensure the integrity of the experiment.

Imagine if our chef used a different type of broth each time he experimented with spices—the results would be all over the place! Control variables keep the experiment grounded and help researchers be confident in their findings.

Confounding Variables Imagine a hidden rock in a stream, changing the water’s flow in unexpected ways. Confounding variables are similar—they are external factors that can sneak into experiments and influence the outcome , adding twists to our scientific story.

These variables can blur the relationship between the independent and dependent variables, making the results of the study a bit puzzly. Detecting and controlling these hidden elements helps researchers ensure the accuracy of their findings and reach true conclusions.

There are of course other types of variables, and different ways to manipulate them called " schedules of reinforcement ," but we won't get into that too much here.

Role of the Independent Variable

Manipulation When researchers manipulate the independent variable, they are orchestrating a symphony of cause and effect. They’re adjusting the strings, the brass, the percussion, observing how each change influences the melody—the dependent variable.

This manipulation is at the heart of experimental research. It allows scientists to explore relationships, unravel patterns, and unearth the secrets hidden within the fabric of our universe.

Observation With every tweak and adjustment made to the independent variable, researchers are like seasoned detectives, observing the dependent variable for changes, collecting clues, and piecing together the puzzle.

Observing the effects and changes that occur helps them deduce relationships, formulate theories, and expand our understanding of the world. Every observation is a step towards solving the mysteries of nature and human behavior.

Identifying Independent Variables

Characteristics Identifying an independent variable in the vast landscape of research can seem daunting, but fear not! Independent variables have distinctive characteristics that make them stand out.

They’re the elements that are deliberately changed or controlled in an experiment to study their effects on the dependent variable. Recognizing these characteristics is like learning to spot footprints in the sand—it leads us to the heart of the discovery!

In Different Types of Research The world of research is diverse and varied, and the independent variable dons many guises! In the field of medicine, it might manifest as the dosage of a drug administered to patients.

In psychology, it could take the form of different learning methods applied to study memory retention. In each field, identifying the independent variable correctly is the golden key that unlocks the treasure trove of knowledge and insights.

As we forge ahead on our enlightening journey, equipped with a deeper understanding of independent variables and their roles, we’re ready to delve into the intricate theories and diverse examples that underscore their significance.

Independent Variables in Research

Now that we’re acquainted with the basic concepts and have the tools to identify independent variables, let’s dive into the fascinating ocean of theories and frameworks.

These theories are like ancient scrolls, providing guidelines and blueprints that help scientists use independent variables to uncover the secrets of the universe.

Scientific Method

What is it and How Does it Work? The scientific method is like a super-helpful treasure map that scientists use to make discoveries. It has steps we follow: asking a question, researching, guessing what will happen (that's a hypothesis!), experimenting, checking the results, figuring out what they mean, and telling everyone about it.

Our hero, the independent variable, is the compass that helps this adventure go the right way!

How Independent Variables Lead the Way In the scientific method, the independent variable is like the captain of a ship, leading everyone through unknown waters.

Scientists change this variable to see what happens and to learn new things. It’s like having a compass that points us towards uncharted lands full of knowledge!

Experimental Design

The Basics of Building Constructing an experiment is like building a castle, and the independent variable is the cornerstone. It’s carefully chosen and manipulated to see how it affects the dependent variable. Researchers also identify control and confounding variables, ensuring the castle stands strong, and the results are reliable.

Keeping Everything in Check In every experiment, maintaining control is key to finding the treasure. Scientists use control variables to keep the conditions consistent, ensuring that any changes observed are truly due to the independent variable. It’s like ensuring the castle’s foundation is solid, supporting the structure as it reaches for the sky.

Hypothesis Testing

Making Educated Guesses Before they start experimenting, scientists make educated guesses called hypotheses . It’s like predicting which X marks the spot of the treasure! It often includes the independent variable and the expected effect on the dependent variable, guiding researchers as they navigate through the experiment.

Independent Variables in the Spotlight When testing these guesses, the independent variable is the star of the show! Scientists change and watch this variable to see if their guesses were right. It helps them figure out new stuff and learn more about the world around us!

Statistical Analysis

Figuring Out Relationships After the experimenting is done, it’s time for scientists to crack the code! They use statistics to understand how the independent and dependent variables are related and to uncover the hidden stories in the data.

Experimenters have to be careful about how they determine the validity of their findings, which is why they use statistics. Something called "experimenter bias" can get in the way of having true (valid) results, because it's basically when the experimenter influences the outcome based on what they believe to be true (or what they want to be true!).

How Important are the Discoveries? Through statistical analysis, scientists determine the significance of their findings. It’s like discovering if the treasure found is made of gold or just shiny rocks. The analysis helps researchers know if the independent variable truly had an effect, contributing to the rich tapestry of scientific knowledge.

As we uncover more about how theories and frameworks use independent variables, we start to see how awesome they are in helping us learn more about the world. But we’re not done yet!

Up next, we’ll look at tons of examples to see how independent variables work their magic in different areas.

Examples of Independent Variables

Independent variables take on many forms, showcasing their versatility in a range of experiments and studies. Let’s uncover how they act as the protagonists in numerous investigations and learning quests!

Science Experiments

1) plant growth.

Consider an experiment aiming to observe the effect of varying water amounts on plant height. In this scenario, the amount of water given to the plants is the independent variable!

2) Freezing Water

Suppose we are curious about the time it takes for water to freeze at different temperatures. The temperature of the freezer becomes the independent variable as we adjust it to observe the results!

3) Light and Shadow

Have you ever observed how shadows change? In an experiment, adjusting the light angle to observe its effect on an object’s shadow makes the angle of light the independent variable!

4) Medicine Dosage

In medical studies, determining how varying medicine dosages influence a patient’s recovery is essential. Here, the dosage of the medicine administered is the independent variable!

5) Exercise and Health

Researchers might examine the impact of different exercise forms on individuals’ health. The various exercise forms constitute the independent variable in this study!

6) Sleep and Wellness

Have you pondered how the sleep duration affects your well-being the following day? In such research, the hours of sleep serve as the independent variable!

7) Learning Methods

Psychologists might investigate how diverse study methods influence test outcomes. Here, the different study methods adopted by students are the independent variable!

8) Mood and Music

Have you experienced varied emotions with different music genres? The genre of music played becomes the independent variable when researching its influence on emotions!

9) Color and Feelings

Suppose researchers are exploring how room colors affect individuals’ emotions. In this case, the room colors act as the independent variable!

Environment

10) rainfall and plant life.

Environmental scientists may study the influence of varying rainfall levels on vegetation. In this instance, the amount of rainfall is the independent variable!

11) Temperature and Animal Behavior

Examining how temperature variations affect animal behavior is fascinating. Here, the varying temperatures serve as the independent variable!

12) Pollution and Air Quality

Investigating the effects of different pollution levels on air quality is crucial. In such studies, the pollution level is the independent variable!

13) Internet Speed and Productivity

Researchers might explore how varying internet speeds impact work productivity. In this exploration, the internet speed is the independent variable!

14) Device Type and User Experience

Examining how different devices affect user experience is interesting. Here, the type of device used is the independent variable!

15) Software Version and Performance

Suppose a study aims to determine how different software versions influence system performance. The software version becomes the independent variable!

16) Teaching Style and Student Engagement

Educators might investigate the effect of varied teaching styles on student engagement. In such a study, the teaching style is the independent variable!

17) Class Size and Learning Outcome

Researchers could explore how different class sizes influence students’ learning. Here, the class size is the independent variable!

18) Homework Frequency and Academic Achievement

Examining the relationship between the frequency of homework assignments and academic success is essential. The frequency of homework becomes the independent variable!

19) Telescope Type and Celestial Observation

Astronomers might study how different telescopes affect celestial observation. In this scenario, the telescope type is the independent variable!

20) Light Pollution and Star Visibility

Investigating the influence of varying light pollution levels on star visibility is intriguing. Here, the level of light pollution is the independent variable!

21) Observation Time and Astronomical Detail

Suppose a study explores how observation duration affects the detail captured in astronomical images. The duration of observation serves as the independent variable!

22) Community Size and Social Interaction

Sociologists may examine how the size of a community influences social interactions. In this research, the community size is the independent variable!

23) Cultural Exposure and Social Tolerance

Investigating the effect of diverse cultural exposure on social tolerance is vital. Here, the level of cultural exposure is the independent variable!

24) Economic Status and Educational Attainment

Researchers could explore how different economic statuses impact educational achievements. In such studies, economic status is the independent variable!

25) Training Intensity and Athletic Performance

Sports scientists might study how varying training intensities affect athletes’ performance. In this case, the training intensity is the independent variable!

26) Equipment Type and Player Safety

Examining the relationship between different sports equipment and player safety is crucial. Here, the type of equipment used is the independent variable!

27) Team Size and Game Strategy

Suppose researchers are investigating how the size of a sports team influences game strategy. The team size becomes the independent variable!

28) Diet Type and Health Outcome

Nutritionists may explore the impact of various diets on individuals’ health. In this exploration, the type of diet followed is the independent variable!

29) Caloric Intake and Weight Change

Investigating how different caloric intakes influence weight change is essential. In such a study, the caloric intake is the independent variable!

30) Food Variety and Nutrient Absorption

Researchers could examine how consuming a variety of foods affects nutrient absorption. Here, the variety of foods consumed is the independent variable!

Real-World Examples of Independent Variables

Isn't it fantastic how independent variables play such an essential part in so many studies? But the excitement doesn't stop there!

Now, let’s explore how findings from these studies, led by independent variables, make a big splash in the real world and improve our daily lives!

Healthcare Advancements

31) treatment optimization.

By studying different medicine dosages and treatment methods as independent variables, doctors can figure out the best ways to help patients recover quicker and feel better. This leads to more effective medicines and treatment plans!

32) Lifestyle Recommendations

Researching the effects of sleep, exercise, and diet helps health experts give us advice on living healthier lives. By changing these independent variables, scientists uncover the secrets to feeling good and staying well!

Technological Innovations

33) speeding up the internet.

When scientists explore how different internet speeds affect our online activities, they’re able to develop technologies to make the internet faster and more reliable. This means smoother video calls and quicker downloads!

34) Improving User Experience

By examining how we interact with various devices and software, researchers can design technology that’s easier and more enjoyable to use. This leads to cooler gadgets and more user-friendly apps!

Educational Strategies

35) enhancing learning.

Investigating different teaching styles, class sizes, and study methods helps educators discover what makes learning fun and effective. This research shapes classrooms, teaching methods, and even homework!

36) Tailoring Student Support

By studying how students with diverse needs respond to different support strategies, educators can create personalized learning experiences. This means every student gets the help they need to succeed!

Environmental Protection

37) conserving nature.

Researching how rainfall, temperature, and pollution affect the environment helps scientists suggest ways to protect our planet. By studying these independent variables, we learn how to keep nature healthy and thriving!

38) Combating Climate Change

Scientists studying the effects of pollution and human activities on climate change are leading the way in finding solutions. By exploring these independent variables, we can develop strategies to combat climate change and protect the Earth!

Social Development

39) building stronger communities.

Sociologists studying community size, cultural exposure, and economic status help us understand what makes communities happy and united. This knowledge guides the development of policies and programs for stronger societies!

40) Promoting Equality and Tolerance

By exploring how exposure to diverse cultures affects social tolerance, researchers contribute to fostering more inclusive and harmonious societies. This helps build a world where everyone is respected and valued!

Enhancing Sports Performance

41) optimizing athlete training.

Sports scientists studying training intensity, equipment type, and team size help athletes reach their full potential. This research leads to better training programs, safer equipment, and more exciting games!

42) Innovating Sports Strategies

By investigating how different game strategies are influenced by various team compositions, researchers contribute to the evolution of sports. This means more thrilling competitions and matches for us to enjoy!

Nutritional Well-Being

43) guiding healthy eating.

Nutritionists researching diet types, caloric intake, and food variety help us understand what foods are best for our bodies. This knowledge shapes dietary guidelines and helps us make tasty, yet nutritious, meal choices!

44) Promoting Nutritional Awareness

By studying the effects of different nutrients and diets, researchers educate us on maintaining a balanced diet. This fosters a greater awareness of nutritional well-being and encourages healthier eating habits!

As we journey through these real-world applications, we witness the incredible impact of studies featuring independent variables. The exploration doesn’t end here, though!

Let’s continue our adventure and see how we can identify independent variables in our own observations and inquiries! Keep your curiosity alive, and let’s delve deeper into the exciting realm of independent variables!

Identifying Independent Variables in Everyday Scenarios

So, we’ve seen how independent variables star in many studies, but how about spotting them in our everyday life?

Recognizing independent variables can be like a treasure hunt – you never know where you might find one! Let’s uncover some tips and tricks to identify these hidden gems in various situations.

1) Asking Questions

One of the best ways to spot an independent variable is by asking questions! If you’re curious about something, ask yourself, “What am I changing or manipulating in this situation?” The thing you’re changing is likely the independent variable!

For example, if you’re wondering whether the amount of sunlight affects how quickly your laundry dries, the sunlight amount is your independent variable!

2) Making Observations

Keep your eyes peeled and observe the world around you! By watching how changes in one thing (like the amount of rain) affect something else (like the height of grass), you can identify the independent variable.

In this case, the amount of rain is the independent variable because it’s what’s changing!

3) Conducting Experiments

Get hands-on and conduct your own experiments! By changing one thing and observing the results, you’re identifying the independent variable.

If you’re growing plants and decide to water each one differently to see the effects, the amount of water is your independent variable!

4) Everyday Scenarios

In everyday scenarios, independent variables are all around!

When you adjust the temperature of your oven to bake cookies, the oven temperature is the independent variable.

Or if you’re deciding how much time to spend studying for a test, the study time is your independent variable!

5) Being Curious

Keep being curious and asking “What if?” questions! By exploring different possibilities and wondering how changing one thing could affect another, you’re on your way to identifying independent variables.

If you’re curious about how the color of a room affects your mood, the room color is the independent variable!

6) Reviewing Past Studies

Don’t forget about the treasure trove of past studies and experiments! By reviewing what scientists and researchers have done before, you can learn how they identified independent variables in their work.

This can give you ideas and help you recognize independent variables in your own explorations!

Exercises for Identifying Independent Variables

Ready for some practice? Let’s put on our thinking caps and try to identify the independent variables in a few scenarios.

Remember, the independent variable is what’s being changed or manipulated to observe the effect on something else! (You can see the answers below)

Scenario One: Cooking Time

You’re cooking pasta for dinner and want to find out how the cooking time affects its texture. What is the independent variable?

Scenario Two: Exercise Routine

You decide to try different exercise routines each week to see which one makes you feel the most energetic. What is the independent variable?

Scenario Three: Plant Fertilizer

You’re growing tomatoes in your garden and decide to use different types of fertilizer to see which one helps them grow the best. What is the independent variable?

Scenario Four: Study Environment

You’re preparing for an important test and try studying in different environments (quiet room, coffee shop, library) to see where you concentrate best. What is the independent variable?

Scenario Five: Sleep Duration

You’re curious to see how the number of hours you sleep each night affects your mood the next day. What is the independent variable?

By practicing identifying independent variables in different scenarios, you’re becoming a true independent variable detective. Keep practicing, stay curious, and you’ll soon be spotting independent variables everywhere you go.

Independent Variable: The cooking time is the independent variable. You are changing the cooking time to observe its effect on the texture of the pasta.

Independent Variable: The type of exercise routine is the independent variable. You are trying out different exercise routines each week to see which one makes you feel the most energetic.

Independent Variable: The type of fertilizer is the independent variable. You are using different types of fertilizer to observe their effects on the growth of the tomatoes.

Independent Variable: The study environment is the independent variable. You are studying in different environments to see where you concentrate best.

Independent Variable: The number of hours you sleep is the independent variable. You are changing your sleep duration to see how it affects your mood the next day.

Whew, what a journey we’ve had exploring the world of independent variables! From understanding their definition and role to diving into a myriad of examples and real-world impacts, we’ve uncovered the treasures hidden in the realm of independent variables.

The beauty of independent variables lies in their ability to unlock new knowledge and insights, guiding us to discoveries that improve our lives and the world around us.

By identifying and studying these variables, we embark on exciting learning adventures, solving mysteries and answering questions about the universe we live in.

Remember, the joy of discovery doesn’t end here. The world is brimming with questions waiting to be answered and mysteries waiting to be solved.

Keep your curiosity alive, continue exploring, and who knows what incredible discoveries lie ahead.

Related posts:

• Confounding Variable in Psychology (Examples + Definition)
• 19+ Experimental Design Examples (Methods + Types)
• Variable Interval Reinforcement Schedule (Examples)
• Variable Ratio Reinforcement Schedule (Examples)
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The Scientific Method/Independent and Dependent Variables

• 1 Relationships Between Variables
• 2 Hypothesis
• 3.1 Corollary to Isolation of Effects

Relationships Between Variables

In any experiment, the object is to gather information about some event, in order to increase one's knowledge about it. In order to design an experiment, it is necessary to know or make an educated guess about cause and effect relationships between what you change in the experiment and what you are measuring. In order to do this, scientists use established theories to come up with a hypothesis before experimenting.

A hypothesis is a conjecture, based on knowledge obtained while formulating the question, that may explain any given behavior. The hypothesis might be very specific or it might be broad. "DNA makes RNA make protein" or "Unknown species of life dwell in the ocean," are two examples of valid hypothesis.

When formulating a hypothesis in the context of a controlled experiment, it will typically take the form a prediction of how changing one variable effects another, bring a variable any aspect, or collection, open to measurable change. The variable(s) that you alter intentionally in function of the experiment are called independent variables , while the variables that do not change by intended direct action are called dependent variables .

A hypothesis says something to the effect of:

Changing independent variable X should do something to dependent variable Y.

For example, suppose you wanted to measure the effects of temperature on the solubility of table sugar (sucrose). Knowing that dissolving sugar doesn't release or absorb much heat, it may seem intuitive to guess that the solubility does not depend on the temperature. Therefore our hypothesis may be:

Increasing or decreasing the temperature of a solution of water does not affect the solubility of sugar.

Isolation of Effects

When determining what independent variables to change in an experiment, it is very important that you isolate the effects of each independent variable. You do not want to change more than one variable at once, for if you do it becomes more difficult to analyze the effects of each change on the dependent variable.

This is why experiments have to be designed very carefully. For example, performing the above tests on tap water may have different results from performing them on spring water, due to differences in salt content. Also, performing them on different days may cause variation due to pressure differences, or performing them with different brands of sugar may yield different results if different companies use different additives.

It is valid to test the effects of each of these things, if one desires, but if one does not have an infinite amount of money to experiment with all of the things that could go wrong (to see what happens if they do), a better alternative is to design the experiment to avoid potential pitfalls such as these.

Corollary to Isolation of Effects

A corollary to this warning is that when designing the experiment, you should choose a set of conditions that maximizes your power to analyze the effects of changes in variables. For example, if you wanted to measure the effects of temperature and of water volume, you should start with a basis (say, 20oC and 4 fluid ounces of water) which is easy to replicate, and then, keeping one of the variables constant, changing the other one. Then, do the opposite. You may end up with an experimental scheme like this one:

Once the data is gathered, you would analyze tests number 1, 4, and 5 to get an idea of the effect of temperature, and tests number 1, 2, and 3 to get an idea of volume effects. You would not analyze all 5 data points at once.

• Book:The Scientific Method

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Independent and Dependent Variables

In an experiment, the independent variable is the variable that is varied or manipulated by the researcher.

The dependent variable is the response that is measured.   One way to think about it is that the dependent variable depends on the change in the independent variable.  In theory, a change in the independent variable will lead to a change in the dependent variable.

In a study of how different doses of a drug affect the severity of symptoms, a researcher could compare the frequency and intensity of symptoms when different doses are administered.

Here the independent variable is the dose and the dependent variable is the frequency/intensity of symptoms .

The rudder on a boat directs the course of the boat.  By changing the position of the rudder (turning it left or right), the rudder moves a certain way in the water, and that movement changes the trajectory of the boat.  

Here the independent variable is the rudder , while the dependent variable is the trajectory of the boat.

Tips: 

Independent and dependent variables are often referred to in other ways.  For instance, independent variables are sometimes called experimental variables or predictor variables.  Dependent variables are sometimes called outcome variables.

One way to differentiate between whether a variable is independent or dependent is to consider when each variable occurred.  Typically, the independent variable will be the variable that happened earlier. Meaning, if I am looking at a dataset that has a variable for the year someone was born and a variable for their level of happiness in 2019, it’s a good bet that the birth year is the independent variable because it happened before the current measure of happiness in 2019 (assuming we are not surveying newborn babies). In effect, this question would be measuring whether someone’s year of birth (maybe translated as generation affiliation) relates to how happy they are in 2019.

• << Previous: Qualitative vs. Quantitative
• Last Updated: Aug 16, 2021 1:10 PM
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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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Chloe Campbell Education

Resources for your classroom

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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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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