In: Statistics and Probability
Describe the conditions in which a nonparametric test would be a better selection than a parametric test. Illustrate your ideas with a specific example of when you would use each type of test using similar variables for each example.
1.A parametric statistical test is one that makes assumptions about the parameters (defining properties) of the population distribution(s) from which one's data are drawn, while a non-parametric test is one that makes no such assumptions.
2.A Parametric tests are those that make assumptions about the parameters of the population distribution from which the sample is drawn. This is often the assumption that the population data are normally distributed.
Non-parametric tests are “distribution-free” and, as such, can be used for non-Normal variables.
IF SOME ASSUMPTIONS OF PARAMETRIC TESTS ARE NOT FOLLOWED THEN WE MOVE TO NON-PARAMETRIC TEST ,SOME ARE FOLLOWING ALTERNATIVE NON-PARAMETRIC TEST FOR PARAMETRIC TEST.
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