Statistical power refers to the probability of correctly rejecting a null hypothesis (a hypothesis of no difference). Failing to reject a false null hypothesis means that the researcher will erroneously conclude that a particular treatment, intervention, or relationship is not important. Statistical power is influenced by three factors: (1) the alpha level (α, or probability value) adopted for the statistical test, (2) the size of the sample, and (3) the effect size (ES; or the magnitude of the observed effect). Before discussing these factors, a few words must be said about Type I and Type II errors in hypothesis testing.

Type I and Type II Errors

Figure 1 shows the interplay of accepting or rejecting a null hypothesis when it is actually true or false. A ...

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