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ANOVA 的功效分析×独立样本t检验×
领域统计学统计学
方法族Hypothesis testHypothesis test
起源年份19881908
提出者Jacob CohenStudent (W. S. Gosset)
类型Sample size determinationParametric mean comparison
开创性文献Cohen, 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 ↗
别名ANOVA 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
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摘要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.
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ScholarGate方法对比: Power Analysis for ANOVA · Independent t-test. 于 2026-06-19 检索自 https://scholargate.app/zh/compare