Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Muundo Uliohuru Kabisa (CRD)× | Kruskal-Wallis H test× | Uchanganuzi wa Faulo wa Njia Moja× | |
|---|---|---|---|
| Nyanja≠ | Muundo wa Majaribio | Takwimu | Takwimu |
| Familia | Hypothesis test | Hypothesis test | Hypothesis test |
| Mwaka wa asili≠ | 1935 | 1952 | 1925 |
| Mwanzilishi≠ | R. A. Fisher | William Kruskal & W. Allen Wallis | Ronald A. Fisher |
| Aina≠ | Parametric group comparison via one-way ANOVA | Nonparametric group comparison | Parametric mean comparison |
| Chanzo asilia≠ | 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 ↗ | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| Majina mbadala | 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 | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| Zinazohusiana≠ | 3 | 5 | 4 |
| Muhtasari≠ | 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. | 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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