What is the purpose of a chi-square test in statistics?

The purpose of a chi-square test is to evaluate significant associations between categorical variables. This statistical method is particularly useful for determining whether the frequencies of observations in different categories differ from what would be expected under a certain hypothesis of independence. For example, it might be applied to determine whether gender is associated with voting preference. The test calculates a chi-square statistic based on the difference between observed and expected frequencies, enabling researchers to ascertain if the associations are statistically significant or if they can be attributed to random chance.

This focus on categorical data is distinct from other statistical methods that revolve around continuous data or estimating population parameters, which often involve different types of tests and analyses. By centering on the relationship between two or more categorical variables, the chi-square test plays a crucial role in various fields, such as social sciences and epidemiology, where understanding the relationship between groups is paramount.