Comparer des méthodes

	Analyse de puissance statistique pour la corrélation de Pearson	Corrélation de Pearson par le produit des moments
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1988	1895
Auteur d'origine	Jacob Cohen	Karl Pearson
Type	Sample size / power determination	Parametric correlation
Source fondatrice	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.
Alias	Korelasyon Güç Analizi, power analysis for r, sample size for correlation	pearson r, product-moment correlation, bivariate correlation, Pearson Korelasyon Analizi
Apparentées	4	4
Résumé	Correlation power analysis is a pre-study calculation that determines how many participants are needed — or how much statistical power an existing sample provides — for a Pearson correlation test. Formalised by Jacob Cohen in his landmark 1988 text, it uses the expected correlation coefficient r directly as the effect size, so researchers can plan studies that are neither underpowered nor wastefully large.	The Pearson product-moment correlation coefficient (r) is a parametric measure of the direction and strength of the linear association between two continuous variables. Introduced by Karl Pearson in 1895, it remains the most widely used bivariate correlation statistic in the social, health, and natural sciences. The coefficient ranges from −1 (perfect negative linear relationship) to +1 (perfect positive), with 0 indicating no linear association.