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t检验的功效分析×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19691908
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t-test power analysis, sample size calculation for t-test, Güç Analizi — t-Testistudent t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
相关54
摘要Power analysis for the t-test is a sample size planning procedure that determines how many participants are required to detect a mean difference of a given magnitude with acceptable probability. Formalised by Jacob Cohen in his 1969 and 1988 editions of Statistical Power Analysis for the Behavioral Sciences, it links four quantities — effect size (Cohen's d), significance level (α), statistical power (1 − β), and sample size — so that fixing any three allows calculation of the fourth.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 t-test · Independent t-test. 于 2026-06-19 检索自 https://scholargate.app/zh/compare