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Størrelsesanalyse for ANOVA×Uavhengig utvalg t-test×
FagfeltStatistikkStatistikk
FamilieHypothesis testHypothesis test
Opprinnelsesår19881908
OpphavspersonJacob CohenStudent (W. S. Gosset)
TypeSample size determinationParametric mean comparison
Opprinnelig kildeCohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗
AliasANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVAstudent t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
Relaterte44
SammendragPower 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.
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ScholarGateSammenlign metoder: Power Analysis for ANOVA · Independent t-test. Hentet 2026-06-19 fra https://scholargate.app/no/compare