Categorical data analysis is the analysis of data where the response variable has been grouped into a set of mutually exclusive ordered (such as age group) or unordered (such as eye color) categories.
Categorical (or discrete) variables are used to organize observations into groups that share a common trait. The trait may be nominal (e.g., sex or eye color) or ordinal (e.g., age group), and, in general, the number of groups within a variable is 20 or fewer (Imrey & Koch, 2005). Most statistical procedures distinguish between independent, or explanatory, and dependent, or response, variables. For instance, an analysis of variancemay be used to determine how a continuous response variable varies according to explanatory variable levels such as eye color. In contrast, categorical data analysis involves the statistical treatment of categorical response variables. Because the distributional assumptions for categorical variables are different from continuous.
