In this experiment, the was intentionally manipulated. this was the independent variable.

The two main variables in a science experiment are the independent variable and the dependent variable. Here's the definition on independent variable and a look at how it's used:

  • The independent variable is the factor that you purposely change or control in order to see what effect it has.
  • The variable that responds to the change in the independent variable is called the dependent variable. It depends on the independent variable.
  • The independent variable is graphed on the x-axis.

An independent variable is defines as the variable that is changed or controlled in a scientific experiment. It represents the cause or reason for an outcome.
Independent variables are the variables that the experimenter changes to test their dependent variable. A change in the independent variable directly causes a change in the dependent variable. The effect on the dependent variable is measured and recorded.

Common Misspellings: independant variable

  • A scientist is testing the effect of light and dark on the behavior of moths by turning a light on and off. The independent variable is the amount of light and the moth's reaction is the dependent variable.
  • In a study to determine the effect of temperature on plant pigmentation, the independent variable (cause) is the temperature, while the amount of pigment or color is the dependent variable (the effect).

When graphing data for an experiment, the independent variable is plotted on the x-axis, while the dependent variable is recorded on the y-axis. An easy way to keep the two variables straight is to use the acronym DRY MIX, which stands for:

  • Dependent variable that Responds to change goes on the Y axis
  • Manipulated or Independent variable goes on the X axis

Students are often asked to identify the independent and dependent variable in an experiment. The difficulty is that the value of both of these variables can change. It's even possible for the dependent variable to remain unchanged in response to controlling the independent variable.

Example: You're asked to identify the independent and dependent variable in an experiment looking to see if there is a relationship between hours of sleep and student test scores.

There are two ways to identify the independent variable. The first is to write the hypothesis and see if it makes sense:

  • Student test scores have no effect on the number of hours the students sleeps.
  • The number of hours students sleep have no effect on their test scores.

Only one of these statements makes sense. This type of hypothesis is constructed to state the independent variable followed by the predicted impact on the dependent variable. So, the number of hours of sleep is the independent variable.

The other way to identify the independent variable is more intuitive. Remember, the independent variable is the one the experimenter controls to measures its effect on the dependent variable. A researcher can control the number of hours a student sleeps. On the other hand, the scientist has no control on the students' test scores.

The independent variable always changes in an experiment, even if there is just a control and an experimental group. The dependent variable may or may not change in response to the independent variable. In the example regarding sleep and student test scores, it's possible the data might show no change in test scores, no matter how much sleep students get (although this outcome seems unlikely). The point is that a researcher knows the values of the independent variable. The value of the dependent variable is measured.

  • Babbie, Earl R. (2009). The Practice of Social Research (12th ed.). Wadsworth Publishing. ISBN 0-495-59841-0.
  • Dodge, Y. (2003). The Oxford Dictionary of Statistical Terms. OUP. ISBN 0-19-920613-9.
  • Everitt, B. S. (2002). The Cambridge Dictionary of Statistics (2nd ed.). Cambridge UP. ISBN 0-521-81099-X.
  • Gujarati, Damodar N.; Porter, Dawn C. (2009). "Terminology and Notation". Basic Econometrics (5th international ed.). New York: McGraw-Hill. p. 21. ISBN 978-007-127625-2.
  • Shadish, William R.; Cook, Thomas D.; Campbell, Donald T. (2002). Experimental and quasi-experimental designs for generalized causal inference. (Nachdr. ed.). Boston: Houghton Mifflin. ISBN 0-395-61556-9.

Any factor that can take on different values in an experiment is a scientific variable.

For example, in an experiment investigating the effectiveness of a new training program, the variables might be:

  • Final test scores
  • Student age
  • Time spent on the training program
  • Time to complete final test
  • Student gender
  • Student ratings of the training program 

Depending on how the researcher operationalizes all the variables in an experiment, the above could be either dependent or independent variables.

It’s the research design that decides which variables are manipulated and which are measured as a result of that manipulation.

What is the Independent Variable?

The independent variable is "independent" because its variation does not depend on the variation of another variable in the experiment/research project. The independent variable is controlled or changed only by the researcher. This factor is often the research question/hypothesis behind the outcome of the experiment.

In this experiment, the was intentionally manipulated. this was the independent variable.

In the above example, the researcher may have wanted to see if participating in the training program raised students' scores on a final test.

Mini-quiz 1

Can you identify the independent variable in this experiment?

  1. Score on the test
  2. Time spent on the training program
  3. Participation on the training program

What do you think is correct? The answer is at the bottom of the article.

How Many Independent Variables Do You Test?

There are often not more than one or two independent variables tested in an experiment, otherwise it is difficult to determine the influence of each upon the final results. There may be several dependent variables, because manipulating the independent variable can influence many different things.

In this experiment, the was intentionally manipulated. this was the independent variable.

For example, an experiment to test the effects of a certain fertilizer on plant growth could measure height, number of fruits and the average weight of the fruit produced. All of these are valid analyzable factors arising from the manipulation of one independent variable, the amount of fertilizer.

In this experiment, the was intentionally manipulated. this was the independent variable.

Potential Complexities of the Independent Variable

The term independent variable is often a source of confusion; many people assume that the name means that the variable is independent of any manipulation. The name arises because the variable is isolated from any other factor, allowing experimental manipulation to establish analyzable results.

A useful acronym is DRY-MIX. This helps you remember which axis to plot your data should you need to draw a graph:

  • D - Dependent
  • R - Responding
  • Y - Y-axis

  • - Manipulated
  • - Independent
  • - X-axis

Some research papers appear to give results manipulating more than one experimental variable, but this is usually a false impression.

Each manipulated variable is likely to be an experiment in itself, one area where the words 'experiment' and 'research' differ. It is simply more convenient for the researcher to bundle them into one paper, and discuss the overall results.

The researcher above might also study the effects of temperature, or the amount of water on growth, but these must be performed as discrete experiments, with only the conclusion and discussion amalgamated at the end.

Examples of the Independent Variable

Jane Elliott's Anti-Racism Experiment

Third grade teacher Jane Elliott’s famous experiment involved dividing her class into two groups: blue-eyed and brown-eyed children. She gave the blue-eyed children extra privileges and emphasized how superior they were to the brown-eyed, who were now a “minority group.”

As a result, the brown-eyed children saw a drop in confidence, academic performance and an increase in bullying. However, when she later labelled the blue-eyed group as the inferior, these effects were reversed.

Here, the independent variable was group status, i.e. whether the children where in the privileged group or not. This had various observable effects on the children. Importantly, the eye color of the children was not the independent variable here. Eye color was an arbitrary choice made by the teacher to draw parallels to racism and prejudice.

Mini-quiz 2

Can you identify a possible dependent variable in this experiment? 

  1. Level of bullying
  2. Academic performance 
  3. Confidence level
  4. All of the above

What do you think is correct? The answer is at the bottom of the article.

Bandura Bobo Doll Experiment

In the Bandura Bobo Doll experiment, whether the children were exposed to an aggressive adult, or to a passive adult, was the independent variable.

This experiment is a prime example of how the concept of experimental variables can become a little complex. Bandura also studied the differences between boys and girls, with gender as an independent variable. Surely, this is breaking the rules of only having one manipulated variable!

In fact, this is a prime example of performing multiple experiments at the same time. If you study the structure of the research design, you will see that the Bobo Doll Experiment should have been called the Bobo Doll Experiments.

It was actually four experiments, each with their own hypothesis and variables, running concurrently. It would have been expensive, and possibly unethical, to test the children four times and, if the same children were used each time, their behavior may have changed with repetition.

Careful design allowed Bandura to test different hypotheses as part of the same research.

Mini-quiz 3

Can you identify the separate independent variables in this experiment? Pick two.

  1. Presence or absence of Bobo doll
  2. Gender of the role models
  3. Aggressiveness of the role models
  4. Number of children

The answer is at the bottom of the article.

Mini-quiz Answers:

Mini-quiz 1

Can you identify the independent variable in this experiment?

Option 3. Participation on the training program.

The researcher could manipulate the variable of whether students participated on the program or not, then measure the results, for example their score on a final test.

Mini-quiz 2

Can you identify a possible dependent variable in this experiment?

Option 4. All of the above.

The experiment measured the children's overall behavior. But this could have been broken into separate dependent variables, for example academic performance, level of bullying, or confidence levels. 

Mini-quiz 3

Can you identify the separate independent variables in this experiment? Pick two.

Option 2 and 3. The gender of the role models and the aggressiveness of the role models.

Bandura was interested to see if a child would imitate their role model, but he also wanted to see if a child was more likely to imitate them if they were of the same gender.