Independent and dependent variables

To research a cause-and-effect relationship, you need to define your independent and dependent variables.

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

If you think an outcome has multiple causes, you can include multiple independent variables; if you want to study a variety of effects, you need to measure multiple dependent variables.

Examples of independent and dependent variables
Research QuestionIndependent variable(s)Dependent variable(s)
Do tomatoes grow fastest under fluorescent, incandescent, or natural light?
  • The type of light the tomato plant is grown under
  • The rate of growth of the tomato plant
Do people who live in a city walk more and weigh less than similar individuals in a suburb?
  • Whether someone lives in a city or a suburb
  • Distance walked
  • Weight

Independent and dependent variables in experiments

In experimental research, the independent variable is manipulated or changed by the experimenter to measure the effect of this change on the dependent variable.

Experiment example
You are studying the impact of a new medication on the blood pressure of patients with hypertension (chronic high blood pressure). To test whether the medication is effective, you divide your patients into two groups. One group takes the medication, while the other group takes a sugar pill placebo.

  • Your independent variable is the treatment that you vary between groups: which type of pill the patient receives.
  • Your dependent variable is the outcome that you measure: the blood pressure of the patients.

Independent vs dependent variables

Variables in other types of research

Outside of an experimental setting, researchers cannot directly manipulate or change an independent variable. Instead, they must find already-existing examples of the independent variable and examine how different values change the outcome of the dependent variable.

Research example
You are interested in whether a higher minimum wage impacts the weekly wage growth of workers in the US fast food industry. You look at the wages of fast food employees in two neighboring states, one of which raised its minimum wage last year, while the other did not.

  • Your independent variable is the rise in the minimum wage; although you could not control it yourself, you can make use of the change in your research.
  • Your dependent variable is the difference in weekly wage growth between the two states.

In non-experimental contexts, independent and dependent variables are sometimes referred to by different terms.

Other names for independent variables

In some types of research, the variable you think is the cause might not be fully independent. In this case, you might use one of these terms:

  • 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).

Other names for dependent variables

Dependent variables are also known by these terms:

  • 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)

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Visualizing independent and dependent variables

Researchers often use charts or graphs to visualize the results of their studies. The norm is to place the independent variable on the “x”or horizontal axis and the dependent variable on the “y” or vertical axis.

For instance, how might a graph look from our example study on the impact of a new medication on blood pressure?

Visualizing independent and dependent variables on a graph

Frequently asked questions

What are independent and dependent variables?

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause, while a dependent variable is the effect.

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

  • The independent variable is the amount of nutrients added to the crop field.
  • The dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design.

Why are independent and dependent variables important?

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.

What is an example of an independent and a 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.
Can a variable be both independent and dependent?

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!

Can I include more than one independent or dependent variable in a study?

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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Lauren Thomas

Lauren has a bachelor's degree in Economics and Political Science and is currently finishing up a master's in Economics. She is always on the move, having lived in five cities in both the US and France, and is happy to have a job that will follow her wherever she goes.

2 comments

Tata Ahmad
July 25, 2020 at 8:41 PM

Hi my question is that
I need more and easy way of how can I identify kind of sampling in research question

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Shona McCombes
Shona McCombes (Scribbr-team)
July 29, 2020 at 7:44 PM

Hi,

Our articles on sampling methods and research questions might be helpful to you.

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