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- W3180080 abstract "This chapter discusses nonparametric and distribution-free methods. The main advantage of nonparametric and distribution-free statistical tests is that they do not require the population(s) being sampled to be normally distributed, and therefore, are applicable when gross nonnormality is suspected. The primary disadvantage of these methods is that when normality does exist, they are less powerful than the corresponding parametric tests. The power efficiency of a nonparametric or distribution-free test is almost always less than 100%, and sometimes much less. Thus it is wasteful to use these methods when parametric tests are applicable. The rank-sum test finds out the difference between the locations of tw o independent samples. The Kruskal-Wallis H test figures out differences among the locations of two or more independent samples. The Wilcoxon test finds out the difference between the locations of two matched samples. The median and sign tests are used primarily to obtain a quick approximation of the results of more powerful tests when samples are large. The median test is used to compare the locations of two or more independent samples. The sign test is used to compare the locations of two or more matched samples." @default.
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- W3180080 date "1976-01-01" @default.
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- W3180080 title "Nonparametric and Distribution-Free Methods" @default.
- W3180080 doi "https://doi.org/10.1016/b978-0-12-743267-0.50026-1" @default.
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