Hypothesis Testing

The method psychologists employ to prove or disprove the validity of their hypotheses.

When psychologists engage in research, they generate specific questions called hypotheses. Research hypotheses are informed speculations about the likely results

of a project. In a typical research design, researchers might want to know whether people in two groups differ in their behavior. For example, psychologists have asked whether the amount that we can remember increases if we can find a way to organize related information. The hypothesis here might be that the organization of related information increases the amount that a person can remember in a learning task.

The researcher knows that such a strategy might have no effect, however. Learning may not change or it may actually worsen. In research, psychologists set up their projects to find out which of two conclusions is more likely, the research hypothesis (i.e., whether organizing related information helps memory) or its complement (i.e., whether organizing related information does not help memory). The possibility that organizing related information will make no difference is called the Null Hypothesis, because it speculates that there may be no change in learning. (The word "null" means "nothing" or "none.") The other possibility, that organizing related information helps to learn, is called the Research Hypothesis or the Alternate Hypothesis. To see which hypothesis is true, people will be randomly assigned to one of two groups that differ in the way they are told to learn. Then the memory of the people in the two groups is compared.

As a rule, psychologists attempt to rule out the Null Hypothesis and to accept the Research Hypothesis because their research typically tries to focus on changes from one situation to the next, not failure to change. In hypothesis testing, psychologists are aware that they may make erroneous conclusions. For example, they might reject the Null Hypothesis and conclude that performance of people in two groups is different, that is, that one group remembers more than the other because they organize the information differently. In reality, one group might have gotten lucky and if the study were performed a second time, the result might be different. In hypothesis testing, this mistaken conclusion is called a Type I error.

Sometimes researchers erroneously conclude that the difference in the way the two groups learn is not important. That is, they fail to reject the Null Hypothesis when they should. This kind of error is called a Type II error. The table below indicates the relationship among errors and correct decisions.

Unfortunately, when researchers conduct a single experiment, they may be making an error without realizing it. This is why other researchers may try to replicate the research of others in order to spot any errors that previous researchers may have made.