ABSTRACT
The most commonly used non-parametric statistics is Chi-square Test of Independence. Since Chi-square is not based on such an assumption, it is an example of a nonparametric or distribution-free test. Chi-square test is used when the data are from two categorical or nominal variables. Chi-square Test of Independence is used when the data are from two categorical variables. Frequently, research data are nominal that is, naming data, such as participants naming the political candidates for whom they plan to vote. Because such data do not consist of scores, they do not directly permit the computation of means and standard deviations. Instead of reporting means and standard deviations for such data, researchers typically report the number of participants who named each category example, named each political candidate and the corresponding percentages. For nominal data, frequencies and percentages are reported instead of means and standard deviations.
