Assumptions on the parameters of the population distribution from which the sample is taken are made in parametric tests. The assumption that the population data are regularly distributed is frequently made. Since non-parametric tests are "distribution-free," they can be applied to variables that are not normal. The Chi-square is robust to the data distribution, much like all other non-parametric statistics. In particular, homoscedasticity in the data or equality of variances among the research groups are not prerequisites. It enables examination of several group studies as well as dichotomous independent variables. A chi-square statistic can only be computed with random, unprocessed, mutually exclusive data that is taken from a sufficiently large sample of independent variables. These requirements are met, for instance, by the outcomes of a fair coin flip. To test hypotheses, chi-square tests are frequently employed. Is this true