What kind of data is used in a Chi Square analysis?

The correct answer is categorical data, which is fundamental to Chi Square analysis. This statistical test is specifically designed to examine the relationships between categorical variables, which represent distinct groups or categories. For instance, categorical data might include responses like "yes" or "no," different types of animals, or various survey responses that can be sorted into categories without any inherent numerical value or order.

When conducting a Chi Square test, researchers assess how observed frequencies of occurrences in each category compare to expected frequencies based on a specific hypothesis. This analysis is particularly useful for understanding whether distributions of categorical data differ from what would be expected due to chance.

Continuous data, on the other hand, consists of numerical values that can represent measurement on a continuum, such as height or weight. Ordinal data involves a ranking or order but does not specify the magnitude of differences between the ranks. Interval data denotes numerical data with specified intervals, but without a true zero point, like temperature in Celsius. While these other types of data are critical in various statistical analyses, they do not align with the underlying assumptions and application of a Chi Square analysis, which is centered on categorical distinctions.