eng
TQMP
Tutorials in Quantitative Methods for Psychology
1913-4126
2007-09-01
3
2
79
79
10.20982/tqmp.03.2.p079
article
A power primer
Cohen, Jacob
jacob.cohen@nyu.edu
1
New York University
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. 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 8 standard statistical tests: (1) the difference between independent means, (2) the significance of a product-moment correlation, (3) the difference between independent rs, (4) the sign test, (5) the difference between independent proportions, (6) chi-square tests for goodness of fit and contingency tables, (7) 1-way analysis of variance (ANOVA), and (8) the significance of a multiple or multiple partial correlation.
https://www.tqmp.org/RegularArticles/vol03-2/p079/p079.pdf
Statistics
statistical power
t-test, correlation and analysis of variance