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| 공분산 분석 (ANCOVA)× | Kruskal-Wallis H 검정× | 일원 분산 분석× | |
|---|---|---|---|
| 분야 | 통계학 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1932 | 1952 | 1925 |
| 창시자≠ | Ronald A. Fisher | William Kruskal & W. Allen Wallis | Ronald A. Fisher |
| 유형≠ | Parametric group comparison with covariate control | Nonparametric group comparison | Parametric mean comparison |
| 원전≠ | 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 ↗ | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| 별칭≠ | 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 | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| 관련≠ | 4 | 5 | 4 |
| 요약≠ | 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. | One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925. |
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