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。
| 完全随机设计 (CRD)× | Kruskal-Wallis H检验× | |
|---|---|---|
| 领域≠ | 实验设计 | 统计学 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 1935 | 1952 |
| 提出者≠ | R. A. Fisher | William Kruskal & W. Allen Wallis |
| 类型≠ | Parametric group comparison via one-way ANOVA | Nonparametric group comparison |
| 开创性文献≠ | Montgomery, D.C. (2017). Design and Analysis of Experiments. Wiley. ISBN: 978-1119320937 | 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 ↗ |
| 别名 | CRD, completely randomised design, one-way experimental design, Tam Tesadüf Deneme Deseni (CRD) | Kruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testi |
| 相关≠ | 3 | 5 |
| 摘要≠ | The completely randomized design is the most fundamental experimental design, in which experimental units are assigned to treatments entirely at random with no restrictions. Analysed by one-way ANOVA, it was formalised by R. A. Fisher in the 1930s and remains the reference starting point for experimental research whenever the experimental material is homogeneous and nuisance variation is absent or negligible. | 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. |
| ScholarGate数据集 ↗ |
|
|