Below you will find complete descriptions and links to 3 different analytics calculators for computing statistical power for analytics studies.

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Compute the observed power for a hierarchical regression study. The calculator computes the observed power for a significance test of the addition of a set of predictor variables B to the hierarchical model, over and above another set of predictor variables A. Knowing whether a model had enough power to detect an expected effect may be useful for analytics studies that rely on hierarchical regression.

Compute the observed power for your multiple regression study, given the observed p-value, the number of predictor variables, the observed R-square, and the sample size. When a regression model is not significant in an analytics study, it may be useful to know whether the model had sufficient power to detect an effect.

Compute the observed power for a one-tailed or two-tailed t-test study, given the observed p-value, the observed effect size, and the total sample size. When a t-based model is not significant in an analytics study, it may be useful to know whether the model had sufficient power to detect the expected or hypothesized effect.