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A chi-square test is a statistical test used to compare observed results with expected results. The purpose of this test is to determine if a difference between observed data and expected data is due to chance, or if it is due to a relationship between the variables you are studying. Therefore, a chi-square test is an excellent choice to help us better understand and interpret the relationship.
Leslie Lea Williams PhD, Kylie Quave PhD, in Quantitative Anthropology, 2019. 10.4 Bivariate Chi-Square Test and Likelihood Ratio. Chi-square tests of independence compare frequencies across tables, assessing whether the distribution of those frequencies is due to chance (Pearson, 1900).In particular, these tests compare the expected frequencies for cells in the table with the observed.