If a health analyst determines the relationship between two categorical variables, which statistical method would be appropriate?

When analyzing the relationship between two categorical variables, the Chi-square test is the most appropriate statistical method. This test assesses whether there is a significant association between the categories of the variables. It compares the observed frequencies in each category to the expected frequencies if there were no association. By calculating the Chi-square statistic, the analyst can determine if the variation in the data is greater than what would be expected by chance, allowing for insights into the relationship between the variables.

In contrast, correlation analysis is typically used for continuous variables to assess the strength and direction of a linear relationship between them. Regression analysis also requires continuous variables, aiming to model the relationship between a dependent variable and one or more independent variables. ANOVA (Analysis of Variance) is used when comparing means across multiple groups, which again typically involves continuous dependent variables rather than categorical ones. Hence, the Chi-square test is specifically designed for categorical data analysis, establishing it as the correct choice for this type of analysis.