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A power primer.

1992/01/01 by Jacob Cohen · 42,496 citations
Agricultural and Biological Sciences · Arts and Humanities · Chemistry · Mathematics · Psychology · #Behavioral and Psychological Studies #Chemistry #Mathematics #Philosophy and History of Science #Physics #Power (physics) #Primer (cosmetics) #Psychology #Sensory Analysis and Statistical Methods #Statistics

paper · doi:10.1037/0033-2909.112.1.155

published in Psychological Bulletin 112(1), 155-159 (American Psychological Association)

openalex publication_date 1992/01/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/06

Abstract

One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.

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