ABSTRACT
When the data collected flagrantly violate the above assumptions, the researcher must select an appropriate nonparametric test. Nonparametric inference tests have fewer requirements or assumptions about population characteristics. For example, to use these tests, it is not necessary to know the means, standard deviations, or shape of the population scores. Because nonparametric tests make no assumptions about the form of the populations from which the test samples were drawn, they are often referred to as distribution-free tests.
