A Quartile Test for Differences in Distribution
作者:
Arnold Barnett,
Ellen Eisen,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1982)
卷期:
Volume 77,
issue 377
页码: 47-51
ISSN:0162-1459
年代: 1982
DOI:10.1080/01621459.1982.10477765
出版商: Taylor & Francis Group
关键词: Two-sample problem;Nonparametric tests
数据来源: Taylor
摘要:
We propose a simple nonparametric statistic using sample quartiles to test differences in distribution. Simulation results suggest that the test is about equal in power over a wide range of alternatives to the familiar procedure of Kolmogorov and Smirnov. When the two distributions compared differ in both location and dispersion, the quartile test may be more sensitive than the Kolmogorov-Smirnov, Wilcoxon rank-sum, Siegel-Tukey, and runs tests.
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