Statistical Power

Abstract One of the most common statistical procedures in the behavioral and social sciences is testing the hypothesis that treatments or interventions have no effect, or that the correlation between two variables is equal to zero—that is, tests of the null hypothesis (H 0 ). There are two ways to make errors when testing a null hypothesis: (1) Type I error, which consists of rejecting the null hypothesis when it is in fact true, and (2) Type II error, which consists of failing to reject the null hypothesis when it is in fact false. Statistical power is defined as 1 minus the conditional probability of making a Type II error. That is, power is the probability of rejecting the null hypothesis when it is in fact false.