Methoden vergleichen

	Power-Analyse für den t-Test	Unabhängiger t-Test für zwei Stichproben
Fachgebiet	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test
Entstehungsjahr	1969	1908
Urheber	Jacob Cohen	Student (W. S. Gosset)
Typ	Sample size determination	Parametric mean comparison
Wegweisende Quelle	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.
Aliasnamen	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
Verwandt	5	4
Zusammenfassung	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.