Confounds in Psychology: Definition & Concept

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  • 0:01 Experimental Design
  • 1:39 What Are Confounds?
  • 3:12 Methods for Reduction
  • 5:02 Lesson Summary
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Lesson Transcript
Instructor: Andrea McKay

Andrea teaches high school AP Psychology and Online Economics and has a Masters degree in Curriculum and Instruction.

In this lesson, you will discover how several different factors, known as confounds, can influence the results of an experiment. You will also learn how researchers work to prevent confounds from ruining the validity of their study.

Experimental Design

During one of your psychology exams, you notice that you feel unusually energized and engaged during the test. When you get your test score back, you are pleased to discover you have scored higher than on any other psychology test you have taken. You start to think about possible causes for your burst of energy, and you recall having an extra cup of coffee before taking the test. Could the caffeine in the coffee be the reason that you were so focused and energized? Perhaps the caffeine helped you score higher. You decide to develop an experiment to find out.

Many research psychologists develop experiments to study human behavior. Experimental design allows psychologists to manipulate a variable and determine how that variable affects behavior. The independent variable is the part of the experiment that is manipulated. The dependent variable is what happens as a result of manipulating the independent variable.

You decide to make half the class the experimental group and give them caffeine before the next test to determine if the caffeine helps them score higher. The other half of the class, the non-caffeinated group, is the control group used to compare against the experimental group. The caffeine is the independent variable, or the part of the experiment that you manipulate. The test scores are the dependent variable, since the scores depend on the treatment of caffeine.

After analyzing your results, you determine the caffeinated group did score significantly higher than the control group. But, can you be sure that the caffeine is the cause of the results?

What Are Confounds?

Confounding variables are factors other than the independent variable that may cause a result. In your caffeine study, for example, it is possible that the students who received caffeine also had more sleep than the control group. Or, the experimental group may have spent more time overall preparing for the exam. Those factors - sleep and extra preparation - could also create a result that has nothing to do with the caffeine. You cannot be sure that the caffeine caused your result instead of the confounding variables. One way to avoid this type of confound is to randomly assign people to the study.

Experimenter bias is another confound that can also affect the results of an experiment. Experimenter bias happens when the experimenter's expectations influence the outcomes of the study. Because you believe that caffeine will help students score higher on a test, you may unintentionally assist the students receiving the caffeine more than the control group when they have questions while taking the test. Your bias could influence the results of the study.

If your subjects know your hypothesis about caffeine and test scores, they may also confound the results by giving you what they believe you want to see. Demand characteristics are clues that subjects receive about the purpose of the study, and if demand characteristics cause subjects to respond as they think they are expected to respond, your results are also invalid and cannot be attributed to caffeine alone.

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