Physical Variables that Affect Internal Validity

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  • 0:06 Internal Validity
  • 1:10 Extraneous Variables
  • 2:35 Physical Variables
  • 4:27 Lesson Summary
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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

How might a researcher accidentally mess up the results of his or her study? In this lesson, we'll look at one type of extraneous variable that can change experimental results - physical or situational variables.

Internal Validity

Sarah is a psychologist, and she wants to know whether tall people are better at math problems than short people. She decides to run an experiment where she gives tall people math problems and compares their results to the performance of short people given the same math test. If the tall people do better than the short people, then she believes she'll have proven that tall people are better than short people at math.

But, what if the tall people that she chooses have taken a lot of math classes and the short people have only taken one or two? What if the tall people are older and therefore better at math than the short people?

In research, internal validity is an important concept. Internal validity is the extent to which a researcher can say that only the independent variable is causing changes in the dependent variable. In Sarah's case, the independent variable is height, and the dependent variable is math skill. If Sarah has a high internal validity, then she can say that height (and only height) is the cause of higher math skill.

Extraneous Variables

But, what if Sarah can't quite say that? Remember that we said that perhaps the taller subjects are actually older and are therefore better at math because their brains have developed more. Or, maybe they've taken more math classes than the short people. Both of these are examples of extraneous variables, or factors other than the independent variable that might cause changes in the dependent variable.

Extraneous variables are dangerous things because they mean that the researcher isn't able to fully prove his or her case. For example, even if the tall people in Sarah's study do better on her math problems, is she able to say that it's because they are better at math? Or, is it because they are older and have had more math classes?

The goal of research is to show that one thing causes another. If there are many extraneous variables in the study, then the researcher is not sure what is causing the changes in the dependent variable. Internal validity is low, and the study is not as good as it could be.

Of course, there are ways to eliminate the impact of extraneous variables. For example, Sarah could make sure that all of the study participants are the same age and that they've all taken the same number of math courses. This will help her control or eliminate the impact of those extraneous variables.

Physical Variables

There are many types of extraneous variables. One type that's easy to control are physical variables, sometimes called situational variables, which are extraneous variables that have to do with the physical space or situation of the experiment. Let's look at an example. What if, in Sarah's study, the tall people were given the math problems in a comfortable room? The room was quiet, at a comfortable temperature and had good lights to see by.

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