Comparer des méthodes

	Analyse de puissance	Test t pour échantillons indépendants
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1969 (1st ed.); 1988 (seminal 2nd ed.)	1908
Auteur d'origine	Jacob Cohen	Student (W. S. Gosset)
Type	Sample size and power planning	Parametric mean comparison
Source fondatrice	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Student (W. S. Gosset) (1908). The probable error of a mean. Biometrika, 6(1), 1–25.
Alias	sample size calculation, power calculation, sensitivity analysis, a priori power analysis	two-sample t-test, unpaired t-test, Student t-test, independent groups t-test
Apparentées	5	4
Résumé	Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (alpha), and statistical power (1 minus beta) — so that researchers can determine the sample size needed before data collection or evaluate the sensitivity of a completed study.	The independent samples t-test is a parametric hypothesis test that determines whether the means of two independent, unrelated groups differ significantly on a continuous outcome variable. Derived from Gosset's 1908 t-distribution, it is one of the most widely used inferential tests in social, behavioral, biomedical, and experimental sciences.