Comparer des méthodes

	Analyse de puissance pour le test t	Test t pour échantillons indépendants
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1969	1908
Auteur d'origine	Jacob Cohen	Student (W. S. Gosset)
Type	Sample size determination	Parametric mean comparison
Source fondatrice	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.
Alias	t-test power analysis, sample size calculation for t-test, Güç Analizi — t-Testi	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
Apparentées	5	4
Résumé	Power analysis for the t-test is a sample size planning procedure that determines how many participants are required to detect a mean difference of a given magnitude with acceptable probability. Formalised by Jacob Cohen in his 1969 and 1988 editions of Statistical Power Analysis for the Behavioral Sciences, it links four quantities — effect size (Cohen's d), significance level (α), statistical power (1 − β), and sample size — so that fixing any three allows calculation of the fourth.	The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances.