The primary purpose of power analysis is to guide in the choice of sample size. First, the experimenter specifies the power that he or she wishes to achieve. Then, the sample size needed for that level of power can be estimated. The calculations for power depend on the size of the effect in the population. Therefore, the first and most difficult step in choosing a sample size is to estimate the size of the effect. If there are published experiments similar to the one to be conducted, then the effects obtained in these published studies can be used as a guide to the size of the effect. There is a need for caution, however, since there is a tendency for published studies to contain overestimates of effect sizes.

Often previous studies are not sufficiently similar to a new study to provide a valid basis for estimating the effect size. In this case, it is possible to specify the minimum effect size that is considered important. For example, an experimenter interested in the effectiveness of a course that prepares students for the quantitative portion of the SAT might consider a difference of 30 points between the treatment group and the control group to be the minimum effect size worth detecting.