Σύγκριση μεθόδων

	Ανάλυση Ισχύος για ANOVA	Ανάλυση Ισχύος για Πολλαπλή Παλινδρόμηση
Πεδίο	Στατιστική	Στατιστική
Οικογένεια	Hypothesis test	Hypothesis test
Έτος προέλευσης	1988	1988
Δημιουργός	Jacob Cohen	Jacob Cohen
Τύπος	Sample size determination	A priori sample size determination
Θεμελιώδης πηγή	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
Εναλλακτικές ονομασίες	ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA	regression power analysis, sample size estimation regression, f² power analysis, Güç Analizi — Regresyon
Συναφείς	4	4
Σύνοψη	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.	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.