Methoden vergelijken

	Poweranalyse voor ANOVA	Onafhankelijke t-toets voor twee steekproeven
Vakgebied	Statistiek	Statistiek
Familie	Hypothesis test	Hypothesis test
Jaar van ontstaan	1988	1908
Grondlegger	Jacob Cohen	Student (W. S. Gosset)
Type	Sample size determination	Parametric mean comparison
Oorspronkelijke bron	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.
Aliassen	ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
Verwant	4	4
Samenvatting	Power analysis for ANOVA is a prospective statistical technique that determines the minimum sample size needed to detect a specified group mean difference with a chosen probability. Formalized by Jacob Cohen in his 1988 monograph, it translates a researcher's effect size expectation — expressed as Cohen's f — along with the desired Type I error rate (alpha) and statistical power (1 − beta) into a concrete per-group sample size recommendation for one-way or factorial ANOVA designs.	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.