Control Groups and Experimental Groups

In a controlled experiment, scientists compare a control group, and an experimental group is identical in all respects except for one difference – experimental manipulation.

Table of Contents

• Differences
• Control Group
• Types of Control Groups
• Experimental Group
• Frequently Asked Questions

Differences

Unlike the experimental group, the control group is not exposed to the independent variable under investigation. So, it provides a baseline against which any changes in the experimental group can be compared.

Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

Almost all experimental studies are designed to include a control group and one or more experimental groups. In most cases, participants are randomly assigned to either a control or experimental group.

Because participants are randomly assigned to either group, we can assume that the groups are identical except for manipulating the independent variable in the experimental group.

It is important that every aspect of the experimental environment is the same and that the experimenters carry out the exact same procedures with both groups so researchers can confidently conclude that any differences between groups are actually due to the difference in treatments.

Control Group

A control group consists of participants who do not receive any experimental treatment. The control participants serve as a comparison group.

The control group is matched as closely as possible to the experimental group, including age, gender, social class, ethnicity, etc.

The difference between the control and experimental groups is that the control group is not exposed to the independent variable, which is thought to be the cause of the behavior being investigated.

Researchers will compare the individuals in the control group to those in the experimental group to isolate the independent variable and examine its impact.

The control group is important because it serves as a baseline, enabling researchers to see what sort of impact changes to the independent variable produce and strengthening researchers’ ability to draw conclusions from a study.

Without the presence of a control group, a researcher cannot determine whether a particular treatment truly has an effect on an experimental group.

Control groups are critical to the scientific method as they help ensure the internal validity of a study.

Example

Assume you want to test a new medication for ADHD. One group would receive the new medication, and the other group would receive a pill that looked exactly the same as the one that the others received, but it would be a placebo. The group that takes the placebo would be the control group.

Types of Control Groups

Positive Control Group

• • A positive control group is an experimental control that will produce a known response or the desired effect.
  • A positive control is used to ensure a test’s success and confirm an experiment’s validity.
  • For example, when testing for a new medication, an already commercially available medication could serve as the positive control.

Negative Control Group

• • A negative control group is an experimental control that does not result in the desired outcome of the experiment.
  • A negative control is used to ensure that there is no response to the treatment and help identify the influence of external factors on the test.
  • An example of a negative control would be using a placebo when testing for a new medication.

Experimental Group

An experimental group consists of participants who are exposed to a particular manipulation of the independent variable. These are the participants who receive the treatment of interest.

Researchers will compare the responses of the experimental group to the responses of a control group to see if the independent variable impacted the participants.

There must be at least one control group and one experimental group in an experiment; however, a single experiment can include multiple experimental groups, which are all compared against the control group.

Having multiple experimental groups enables researchers to vary different levels of an experimental variable and compare the effects of these changes to the control group and among each other.

Example

Assume you want to study to determine if listening to different types of music can help with focus while studying.

You randomly assign participants to one of three groups: one group that listens to music with lyrics, one group that listens to music without lyrics, and another group that listens to no music.

The group of participants listening to no music while studying is the control group, and the groups listening to music, whether with or without lyrics, are the two experimental groups.

Frequently Asked Questions

1. What is the difference between control and experimental groups?

Put simply; an experimental group is a group that receives the variable, or treatment, that the researchers are testing, whereas the control group does not. These two groups should be identical in all other aspects.

2. Do experimental studies always need a control group?

Not all experiments require a control group, but a true “controlled experiment” does require at least one control group. For example, experiments that use a within-subjects design do not have a control group.

In within-subjects designs, all participants experience every condition and are tested before and after being exposed to treatment.

These experimental designs tend to have weaker internal validity as it is more difficult for a researcher to be confident that the outcome was caused by the experimental treatment and not by a confounding variable.

3. Can a study include more than one control group?

Yes, studies can include multiple control groups. For example, if several distinct groups of subjects do not receive the treatment, these would be the control groups.

References

Bailey, R. A. (2008). Design of Comparative Experiments. Cambridge University Press. ISBN 978-0-521-68357-9.

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.