The chi-square test is a nonparametric test of the statistical significance of a relation between two nominal or ordinal variables. Because a chi-square analyzes grosser data than do parametric tests such as t tests and analyses of variance (ANOVAs), the chi-square test can report only whether groups in a sample are significantly different in some measured attribute or behavior; it does not allow one to generalize from the sample to the population from which it was drawn. Nonetheless, because chi-square is less “demanding” about the data it will accept, it can be used in a wide variety of research contexts. This entry focuses on the application, requirements, computation, and interpretation of the chi-square test, along with its role in determining associations among variables.