قارن الطرق

	تحليل القوة لـ ANOVA	اختبار ت للعينات المستقلة
المجال	الإحصاء	الإحصاء
العائلة	Hypothesis test	Hypothesis test
سنة النشأة	1988	1908
صاحب الطريقة	Jacob Cohen	Student (W. S. Gosset)
النوع	Sample size determination	Parametric mean comparison
المصدر التأسيسي	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.
الأسماء البديلة	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
ذات صلة	4	4
الملخص	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.