What does a chi square test of independence assess?

A chi-square test of independence is used to determine whether there is a significant association between two categorical variables. It does this by comparing the observed frequencies of occurrences in a contingency table to the expected frequencies under the assumption that the variables are independent of each other.

When conducting the test, researchers calculate the chi-square statistic, which measures how much the observed counts deviate from what would be expected if there were no relationship between the variables. A significant result indicates that the observed frequencies differ from the expected frequencies to a degree that is unlikely to have occurred by chance, suggesting a potential relationship between the two variables.

This test is not appropriate for continuous variables or for assessing differences in means, which require different statistical methods like t-tests or ANOVA. Instead, the chi-square test is specifically tailored for categorical data, making option C the correct choice in summarizing its purpose.