Módszerek összehasonlítása

	Kruskal-Wallis H-próba	Varianciaanalízis egytényezős	Welch-féle t-próba (egyenlőtlen varianciák)
Tudományterület	Statisztika	Statisztika	Statisztika
Módszercsalád	Hypothesis test	Hypothesis test	Hypothesis test
Keletkezés éve	1952	1925	1947
Megalkotó	William Kruskal & W. Allen Wallis	Ronald A. Fisher	B. L. Welch
Típus	Nonparametric group comparison	Parametric mean comparison	Parametric mean comparison (unequal variances)
Alapmű	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.	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.	Welch, B. L. (1947). The generalization of Student's problem when several different population variances are involved. Biometrika, 34(1/2), 28–35.
Alternatív nevek	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	unequal variances t-test, Welch-Satterthwaite t-test, Welch t-Testi (Eşit Olmayan Varyans)
Kapcsolódó	5	4	4
Összefoglaló	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.	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.