Sammenlign metoder

	Styrkeberegning for multipel regression	Poweranalyse for ANOVA
Fagområde	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test
Oprindelsesår	1988	1988
Ophavsperson	Jacob Cohen	Jacob Cohen
Type	A priori sample size determination	Sample size determination
Oprindelig kilde	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
Aliasser	regression power analysis, sample size estimation regression, f² power analysis, Güç Analizi — Regresyon	ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA
Relaterede	4	4
Resumé	Power analysis for multiple regression is a pre-study procedure, formalised by Jacob Cohen (1988), that calculates the minimum sample size needed to detect a regression effect of a given size with adequate statistical power. It uses the anticipated R² (or the equivalent Cohen's f² effect size) and the number of predictors to determine how many observations must be collected before data collection begins.	Power analysis for ANOVA is a prospective statistical technique that determines the minimum sample size needed to detect a specified group mean difference with a chosen probability. Formalized by Jacob Cohen in his 1988 monograph, it translates a researcher's effect size expectation — expressed as Cohen's f — along with the desired Type I error rate (alpha) and statistical power (1 − beta) into a concrete per-group sample size recommendation for one-way or factorial ANOVA designs.