What is the variable that changes because of some other change in the experiment?

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The two main variables in an experiment are the independent and dependent variable.

An independent variable is the variable that is changed or controlled in a scientific experiment to test the effects on the dependent variable.

A dependent variable is the variable being tested and measured in a scientific experiment.

The dependent variable is 'dependent' on the independent variable. As the experimenter changes the independent variable, the effect on the dependent variable is observed and recorded.

• There can be many variables in an experiment, but the two key variables that are always present are the independent and dependent variable.
• The independent variable is the one that the researcher intentionally changes or controls.
• The dependent variable is the factor that the research measures. It changes in response to the independent variable or depends upon it.

For example, a scientist wants to see if the brightness of light has any effect on a moth being attracted to the light. The brightness of the light is controlled by the scientist. This would be the independent variable. How the moth reacts to the different light levels (distance to light source) would be the dependent variable.

As another example, say you want to know whether or not eating breakfast affects student test scores. The factor under the experimenter's control is the presence or absence of breakfast, so you know it is the independent variable. The experiment measures test scores of students who ate breakfast versus those who did not. Theoretically, the test results depend on breakfast, so the test results are the dependent variable. Note that test scores are the dependent variable, even if it turns out there is no relationship between scores and breakfast.

For another experiment, a scientist wants to determine whether one drug is more effective than another at controlling high blood pressure. The independent variable is the drug, while patient blood pressure is the dependent variable. In some ways, this experiment resembles the one with breakfast and test scores. However, when comparing two different treatments, such as drug A and drug B, it's usual to add another variable, called the control variable. The control variable, which in this case is a placebo that contains the same inactive ingredients as the drugs, makes it possible to tell whether either drug actually affects blood pressure.

The independent and dependent variables may be viewed in terms of cause and effect. If the independent variable is changed, then an effect is seen in the dependent variable. Remember, the values of both variables may change in an experiment and are recorded. The difference is that the value of the independent variable is controlled by the experimenter, while the value of the dependent variable only changes in response to the independent variable.

When results are plotted in graphs, the convention is to use the independent variable as the x-axis and the dependent variable as the y-axis. The DRY MIX acronym can help keep the variables straight:

D is the dependent variable
R is the responding variable
Y is the axis on which the dependent or responding variable is graphed (the vertical axis)

M is the manipulated variable or the one that is changed in an experiment
I is the independent variable
X is the axis on which the independent or manipulated variable is graphed (the horizontal axis)

• The independent and dependent variables are the two key variables in a science experiment.
• The independent variable is the one the experimenter controls. The dependent variable is the variable that changes in response to the independent variable.
• The two variables may be related by cause and effect. If the independent variable changes, then the dependent variable is affected.

• Carlson, Robert (2006). A concrete introduction to real analysis. CRC Press, p.183.
• Dodge, Y. (2003) The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-920613-9.
• 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.
• Quine, Willard V. (1960). "Variables Explained Away". Proceedings of the American Philosophical Society. American Philosophical Society. 104 (3): 343–347. 

Updated February 10, 2020

By Riti Gupta

Reviewed by: Lana Bandoim, B.S.

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.

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.

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.

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.

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.

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)?

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!