What type of data does a chi-square test use?

A chi-square test specifically analyzes nominal or qualitative data. This type of data consists of categories or groups without any inherent order. For instance, data might represent gender, ethnicity, or a specific condition (such as "yes" or "no" responses). The goal of a chi-square test is to determine if there is a significant association between categorical variables, such as whether different types of treatments lead to varying outcomes in symptom occurrences.

In contrast, quantitative data involves numeric values and measurements, which aren't suitable for chi-square tests. Ordinal data, while it has a rank order, does not provide measurable distances between the ranks, making it less appropriate for this test than nominal data. Interval data, characterized by measurable distances and no true zero point, is also not fitting for chi-square analysis because it involves continuous variables rather than categorical ones.