Categorical Data Analysis

TL;DR

This paper provides an overview of fundamental methods for analyzing categorical data, including contingency tables, hypothesis testing, and measures of association, with practical examples from social science and health research.

Contribution

It offers a comprehensive introduction to categorical data analysis techniques, filling a gap in introductory statistics education.

Findings

Illustrates analysis of contingency tables with real data

Demonstrates hypothesis testing and measures of association

Provides practical examples from social and health sciences

Abstract

Categorical data are common in educational and social science research; however, methods for its analysis are generally not covered in introductory statistics courses. This chapter overviews fundamental concepts and methods in categorical data analysis. It describes and illustrates the analysis of contingency tables given different sampling processes and distributions, estimation of probabilities, hypothesis testing, measures of associations, and tests of no association with nominal variables, as well as the test of linear association with ordinal variables. Three data sets illustrate fatal police shootings in the United States, clinical trials of the Moderna vaccine, and responses to General Social Survey questions.