Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Двофакторний дисперсійний аналіз (Two-Way ANOVA)× | Дисперсійний аналіз з коваріатою (ANCOVA)× | Крускала-Волліса H-критерій× | |
|---|---|---|---|
| Галузь | Статистика | Статистика | Статистика |
| Родина | Hypothesis test | Hypothesis test | Hypothesis test |
| Рік появи≠ | 1925 | 1932 | 1952 |
| Автор методу≠ | Ronald A. Fisher | Ronald A. Fisher | William Kruskal & W. Allen Wallis |
| Тип≠ | Parametric factorial mean comparison | Parametric group comparison with covariate control | Nonparametric group comparison |
| Основоположне джерело≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Kruskal, W. H. & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621. DOI ↗ |
| Інші назви≠ | factorial ANOVA, two-factor ANOVA, İki Yönlü ANOVA | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) | Kruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testi |
| Пов'язані≠ | 6 | 4 | 5 |
| Підсумок≠ | Two-Way ANOVA is a parametric hypothesis test that simultaneously examines the main effects of two independent categorical factors and their interaction effect on a single continuous dependent variable. The technique was developed within the broader framework of the analysis of variance established by Ronald A. Fisher in 1925 and remains the standard approach whenever an experiment or survey includes exactly two between-subjects factors. | ANCOVA is a parametric hypothesis test that compares the adjusted means of two or more independent groups while statistically controlling for one or more continuous covariates. By removing the portion of outcome variance explained by the covariate, ANCOVA increases statistical precision and produces fairer group comparisons. The method builds on the general linear model framework consolidated by Fisher in the early 1930s and is described comprehensively by Tabachnick and Fidell (2013). | The Kruskal-Wallis H test is a nonparametric hypothesis test that compares three or more independent groups to decide whether their distributions (typically their medians) differ. Introduced by William Kruskal and W. Allen Wallis in 1952, it works on ranks rather than raw values and is the distribution-free counterpart to one-way ANOVA. |
| ScholarGateНабір даних ↗ |
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