Doing tests for differences in data in two categorical variables

Categorical output variables, also known as response variables or dependent variables, are variables that take on discrete values from a finite set of possible outcomes. We can consider that there are two types of categorical variables: nominal and ordinal.

Ordinal variables have a natural ordering among the categories. Examples of ordinal variables include education level, income bracket, and satisfaction ratings. In linear models, ordinal variables can be represented using their numerical values or by assigning each category a numerical rank. For example, in a linear model predicting job satisfaction based on salary, the ordinal variable income bracket could be assigned a numerical rank from one to five based on the size of the income range. Ranking helps us to use the linear model framework fairly easily.

Nominal variables are variables that have no inherent order or ranking among the categories. Examples of...