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TEST KRUSKAL-WALLIS [1 record]
Record 1 - internal organization data 2006-05-26
Record 1, English
Record 1, Subject field(s)
- Probability (Statistics)
Record 1, Main entry term, English
- Kruskal-Wallis test
1, record 1, English, Kruskal%2DWallis%20test
correct
Record 1, Abbreviations, English
Record 1, Synonyms, English
Record 1, Textual support, English
Record number: 1, Textual support number: 1 DEF
A non-parametric test used to compare three or more samples. 1, record 1, English, - Kruskal%2DWallis%20test
Record number: 1, Textual support number: 1 OBS
The Kruskal-Wallis test [named after William Kruskal and Allen Wallis] is used to test the null hypothesis that all populations have identical distribution functions against the alternative hypothesis that at least two of the samples differ only with respect to location (median), if at all. It is the analogue to the F-test used in analysis of variance. While analysis of variance tests depend on the assumption that all populations under comparison are normally distributed, the Kruskal-Wallis test places no such restriction on the comparison. It is a logical extension of the Wilcoxon-Mann-Whitney Test. 1, record 1, English, - Kruskal%2DWallis%20test
Record 1, French
Record 1, Domaine(s)
- Probabilités (Statistique)
Record 1, Main entry term, French
- test de Kruskal-Wallis
1, record 1, French, test%20de%20Kruskal%2DWallis
correct, masculine noun
Record 1, Abbreviations, French
Record 1, Synonyms, French
Record 1, Textual support, French
Record number: 1, Textual support number: 1 CONT
Le test de Kruskal-Wallis est utilisé lorsqu'il faut décider si les échantillons indépendants sont issus de la même population. C'est donc un test d’identité. Les observations doivent être mesurées sur une échelle numérique ou ordinale(pas nominale). Les échantillons peuvent avoir des nombres d’observations différents. [...] Le test de Kruskal-Wallis peut être perçu comme une généralisation du test de Wilcoxon-Mann-Whitney à plus de deux échantillons. Il est non paramétrique : il ne fait aucune hypothèse sur la forme des distributions sous-jacentes. Comme de nombreux tests non paramétriques, le test de Kruskal-Wallis travaillera non pas sur les valeurs des observations, mais sur leurs rangs, une fois ces observations réunies dans un seul méga-échantillon. La statistique du test de Kruskal-Wallis est construite à partir des moyennes des rangs des observations dans les différents échantillons. 1, record 1, French, - test%20de%20Kruskal%2DWallis
Record 1, Spanish
Record 1, Textual support, Spanish
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