# Understanding Experimental Groups

Scientific experiments often include two groups: the experimental group and the control group. Here's a closer look at the experimental group and how to distinguish it from the experimental group.

### Key Takeaways: Experimental Group

• The experimental group is the set of subjects exposed to a change in the independent variable. While it's technically possible to have a single subject for an experimental group, the statistical validity of the experiment will be vastly improved by increasing the sample size.
• In contrast, the control group is identical in every way to the experimental group, except the independent variable is held constant. It's best to have a large sample size for the control group, too.
• It's possible for an experiment to contain more than one experimental group. However, in the cleanest experiments, only one variable is changed.

## Experimental Group Definition

An experimental group in a scientific experiment is the group on which the experimental procedure is performed. The independent variable is changed for the group and the response or change in the dependent variable is recorded. In contrast, the group that does not receive the treatment or in which the independent variable is held constant is called the control group.

The purpose of having experimental and control groups is to have sufficient data to be reasonably sure the relationship between the independent and dependent variable is not due to chance. If you perform an experiment on only one subject (with and without treatment) or on one experimental subject and one control subject you have limited confidence in the outcome. The larger the sample size, the more probable the results represent a real correlation.

## Example of an Experimental Group

You may be asked to identify the experimental group in an experiment as well as the control group. Here's an example of an experiment and how to tell these two key groups apart.

Let's say you want to see whether a nutritional supplement helps people lose weight. You want to design an experiment to test the effect. A poor experiment would be to take a supplement and see whether or not you lose weight. Why is it bad? You only have one data point! If you lose weight, it could be due to some other factor. A better experiment (though still pretty bad) would be to take the supplement, see if you lose weight, stop taking the supplement and see if the weight loss stops, then take it again and see if weight loss resumes. In this "experiment" you are the control group when you are not taking the supplement and the experimental group when you are taking it.

It's a terrible experiment for a number of reasons. One problem is that the same subject is being used as both the control group and the experimental group. You don't know, when you stop taking treatment, that is doesn't have a lasting effect. A solution is to design an experiment with truly separate control and experimental groups.

If you have a group of people who take the supplement and a group of people who do not, the ones exposed to the treatment (taking the supplement) are the experimental group. The ones not-taking it are the control group.

## How to Tell Control and Experimental Group Apart

In an ideal situation, every factor that affects a member of both the control group and experimental group is exactly the same except for one -- the independent variable. In a basic experiment, this could be whether something is present or not. Present = experimental; absent = control.

Sometimes, it's more complicated and the control is "normal" and the experimental group is "not normal". For example, if you want to see whether or not darkness has an effect on plant growth. Your control group might be plants grown under ordinary day/night conditions. You could have a couple of experimental groups. One set of plants might be exposed to perpetual daylight, while another might be exposed to perpetual darkness. Here, any group where the variable is changed from normal is an experimental group. Both the all-light and all-dark groups are types of experimental groups.

## Sources

Bailey, R.A. (2008). Design of Comparative Experiments. Cambridge: Cambridge University Press. ISBN 9780521683579.

Hinkelmann, Klaus and Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (Second ed.). Wiley. ISBN 978-0-471-72756-9.

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