ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

t检验的功效分析×配对样本 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 (paired)
开创性文献Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE. ISBN: 978-1446249185
别名t-test power analysis, sample size calculation for t-test, Güç Analizi — t-Testidependent samples t-test, repeated measures t-test, matched-pairs t-test, eşleştirilmiş 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 paired samples t-test is a parametric hypothesis test that compares two measurements taken on the same subjects — such as a before and after reading — to decide whether the average change differs from zero. It rests on the t-distribution introduced by Student (W. S. Gosset) in 1908 and works on the within-subject difference scores rather than the raw measurements.
ScholarGate数据集
  1. v1
  2. 1 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Power Analysis for t-test · Paired t-test. 于 2026-06-19 检索自 https://scholargate.app/zh/compare