Approximating power for significance tests with one degree of freedom.

Shortcut approximate equations are described that provide estimates of the sample size required for 50% power (α?=?0.05, two-tailed) for 1 degree of freedom tests of significance for simple correlations, differences between 2 independent group means, and Pearson's chi-square test for 2?×?2 contingency tables. These sample sizes should be thought of as minima, because power equal to 50% means that the chance of a significant finding is that of flipping a fair coin. A more desirable sample size can be computed by simply doubling the 50% sample sizes, which is shown to result in power between 80% and 90%. With these simple tools, power can be estimated rapidly, which, it is hoped, will lead to greater use and understanding of power in the teaching of statistics and in research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)