- Mar 2023
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journals.plos.org journals.plos.org
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Nonparametric statistics are often preferred to parametric tests when the sample size is small and the data are skewed or contain outliers.
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scholarworks.umass.edu scholarworks.umass.edu
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Noteworthy for its longstanding influence is thebook “Nonparametric statistics for the behavioralsciences” by Siege
Highly cited book from 1956!
Siegel (1956) pointed out that traditional parametric tests should not be used with extremely small samples, because these tests have several strong assumptions underlying their use. The t-test requires that observations are drawn from a normally distributed population and the two-sample t-test requires that the two populations have the same variance. According to Siegel (1956), these assumptions cannot be tested when the sample size is small. Siegel (1957) stated that “if samples as small as 6 are used, there is no alternative to using a nonparametric statistical test unless the nature of the population distribution is known exactly” (p. 18).
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- Nov 2020
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statistics.laerd.com statistics.laerd.com
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Assumption #4:
When to choose between the Kruskall-Wallis mean ranks and the median test.
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