Comparer des méthodes

	Analyse de puissance pour le test t	Test t pour échantillons appariés
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 (paired)
Source fondatrice	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE. ISBN: 978-1446249185
Alias	t-test power analysis, sample size calculation for t-test, Güç Analizi — t-Testi	dependent samples t-test, repeated measures t-test, matched-pairs t-test, eşleştirilmiş 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 paired samples t-test is a parametric hypothesis test that compares two measurements taken on the same subjects — such as a before and after reading — to decide whether the average change differs from zero. It rests on the t-distribution introduced by Student (W. S. Gosset) in 1908 and works on the within-subject difference scores rather than the raw measurements.