Categorical Data Analysis I: Associations with nominal and ordinal data

May 23, 2017

Introduction to description and inference for assessing association between variables measured on the nominal or ordinal scale. Practical recommendations for choosing the appropriate procedure for estimating and testing for association. Examples will illustrate use of several software packages, including R, SAS and SPSS. Topics will include:

  • non-model-based measures and tests for nominal/nominal, nominal/ordinal and ordinal/ordinal association
  • dealing with sparse contingency tables
  • treating ordinal data as interval

Prerequisites: Familiarity with material typically covered in an introductory statistics course, including graphical displays, mean and standard deviation, normal distributions, t-tests and confidence intervals, analysis of contingency tables.


Instructor: Dr. Scott Richter is Professor in the Department of Mathematics and Statistics and Director of the UNCG Statistical Consulting Center. He teaches undergraduate and graduate level courses in statistical methodology, and consults extensively with researchers across campus. More information can be found at

Workshop files:

Categorical Data Analysis I


CDA1 SAS code

CDA1_R Code










Contact Us

Quantitative Methodology Series

The University of North Carolina at Greensboro
Department of Mathematics & Statistics
116 Petty Building
PO Box 26170
Greensboro, NC 27402-6170

Scott Richter, Ph.D.

Professor, Department of Mathematics and Statistics
Director of Statistical Consulting Center

John Willse, PSY.D.

Associate Professor and Department Chair, Educational Research Methodology