What does the Chi-square test evaluate?

The Chi-square test is a statistical method used primarily to determine whether there is a significant association between categorical variables. In this context, it evaluates proportions of a categorized outcome by testing the null hypothesis that there is no relationship between the variables in question. This is particularly useful in studies where the data is represented as counts or frequencies across different categories.

For example, if a researcher wants to know if there is a significant difference in the prevalence of a particular condition among different age groups, the Chi-square test would help assess whether the observed frequencies deviate from what would be expected if there were no association.

The other options represent different statistical methods. Evaluating means across groups typically involves t-tests or ANOVA, examining variance between samples relates to tests like Levene's test, and assessing correlation between continuous variables is usually done using techniques like Pearson's correlation coefficient. Thus, B is indeed the most appropriate answer reflecting the function of the Chi-square test.