文章基本信息

标题：A New Transformed t-test for Skewed Data: A Goodness-of-fit Approach
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作者：Khairul Islam ; Tanweer Shapla
期刊名称：International Journal of Statistics and Probability
印刷版ISSN：1927-7032
电子版ISSN：1927-7040
出版年度：2020
卷号：9
期号：5
页码：30-39
DOI：10.5539/ijsp.v9n5p30
出版社：Canadian Center of Science and Education
摘要：A new transformed two-sample t -test has been proposed for testing equality of two population means for skewed distributions by means of a univariate normal goodness of fit to the combined sample. The small sample performance of the proposed test is compared with untransformed t-test and the non-parametric analogue of t-test via Wilcoxon rank sum test using real-life examples and simulation from skewed distributions with varying values of skewness, empirically. It reveals that the proposed new test is appropriate for estimating the level of significance and is more powerful than the untransformed t-test and the Wilcoxon rank sum test for skewed distributions.
关键词：goodness-of-fit;power;transformation;two-sample t-test;Wilcoxon test