非参数统计
Kruskal–Wallis单因素方差分析
统计
Goldfeld–Quandt测试
正态性检验
数学
检验统计量
统计假设检验
统计的
弗里德曼检验
皮尔森卡方检定
考试(生物学)
正态性
计算机科学
曼惠特尼U检验
Z检验
生物
古生物学
作者
Eva Ostertagová,Oskar Ostertag,J. Kováč
出处
期刊:Applied Mechanics and Materials
[Trans Tech Publications, Ltd.]
日期:2014-08-01
卷期号:611: 115-120
被引量:487
标识
DOI:10.4028/www.scientific.net/amm.611.115
摘要
This paper describes the methodology and application of the very popular nonparametric test which is a rank based test named as Kruskal-Wallis. This test is useful as a general nonparametric test for comparing more than two independent samples. It can be used to test whether such samples come from the same distribution. This test is powerful alternative to the one-way analysis of variance. Nonparametric ANOVA has no assumption of normality of random error but the independence of random error is required. If the Kruskal-Wallis statistic is significant, the nonparametric multiple comparison tests are useful methods for further analysis. The statistical analysis of the application data in this paper was performed with software MATLAB.
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