Last Updated 28 Jan 2021

Non Parametric Test

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Non Parametric Test is a kind of statistical test that was discovered by Wolfowitz. This test covers a variety of categories and these are the independent samples, dependent samples and the variables relationship with co- variables. To contrast and differentiate measurements is a hard thing to do, one can choose parametric and nonparametric.

Non parametric test are those tests that has no postulates about arrangement of population. There a number of nonparametric tests and these includes the Mann- Whitney Test, Wilcoxon and the Kruskal- Wallis test. Mann- Whitney Test is comparing two independent random samples. It has its postulates or assumptions and these are the taking of spontaneous segment of populations, autonomy within data’s gathered and its common independence, its scale is ordinal.

The Wilcoxon test or the Wilcoxon signed- rank test is the test that which serves as a replacement of Student’s T test. This was discovered by Frank Wilcoxon. This is comparing a dissimilar measurement that is why it is needed to measure data’s at a gap of measurement. Kruskal- Wallis test, a one way analysis of variance and is used for small samples, it compares unpaired groups. Prism is being used in performing this test.

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These non parametric tests are usually used in ranking order such as movie reviews. But due to lesser postulates, these non parametric tests are full of vigor or vital. Non parametric tests are easy to use and is much simple than the parametric test. This test can be use on determining the population of those depressed people, emotionally disturbed and mentally ill and it can also be used to know the level or the rank of the most significant reasons why people get emotionally unstable and eventually get depressed.

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Non Parametric Test. (2017, May 23). Retrieved from https://phdessay.com/non-parametric-test/

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