Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Планування потужності для t-критерію× | t-критерій Велча (нерівні дисперсії)× | |
|---|---|---|
| Галузь | Статистика | Статистика |
| Родина | Hypothesis test | Hypothesis test |
| Рік появи≠ | 1969 | 1947 |
| Автор методу≠ | Jacob Cohen | B. L. Welch |
| Тип≠ | Sample size determination | Parametric mean comparison (unequal variances) |
| Основоположне джерело≠ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 | Welch, B. L. (1947). The generalization of Student's problem when several different population variances are involved. Biometrika, 34(1/2), 28–35. DOI ↗ |
| Інші назви | t-test power analysis, sample size calculation for t-test, Güç Analizi — t-Testi | unequal variances t-test, Welch-Satterthwaite t-test, Welch t-Testi (Eşit Olmayan Varyans) |
| Пов'язані≠ | 5 | 4 |
| Підсумок≠ | 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. | Welch's t-test is a parametric hypothesis test that compares the means of two independent groups without assuming their variances are equal. It was introduced by B. L. Welch in 1947 as a more robust generalization of Student's two-sample test for situations where the two groups have different spread. |
| ScholarGateНабір даних ↗ |
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