What is the type of data used in the Chi-squared test?

The Chi-squared test is used primarily with nominal data. This type of data consists of categories that do not have a specific order or ranking. The primary purpose of the Chi-squared test is to assess whether there is a significant association between two categorical variables. For instance, researchers might use it to determine if there is a relationship between gender (male, female) and preference for a particular type of product (such as books, electronics, or clothing).

While ordinal, interval, and ratio data all involve some form of measurement that can imply order or a numerical value, they do not fit the categorical nature required for the Chi-squared test. Ordinal data, while it has a rank order, isn't analyzed with Chi-squared because it entails more complex relationships that depend on the distances between ranks. Similarly, interval and ratio data are numerical and are typically analyzed using different statistical techniques that can account for their quantitative nature, such as t-tests or ANOVAs. Therefore, nominal data is uniquely suited for the Chi-squared test, making it the correct answer.