방법 비교

	ANOVA를 위한 검정력 분석	독립 표본 t-검정
분야	통계학	통계학
계열	Hypothesis test	Hypothesis test
기원 연도	1988	1908
창시자	Jacob Cohen	Student (W. S. Gosset)
유형	Sample size determination	Parametric mean comparison
원전	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.
별칭	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
관련	4	4
요약	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.