While graphical display techniques are common adjuncts to analysis of variance and regression, methods for plotting contingency table data are not as widely used. Moreover, while statistical methods can be used to determine which variables are related, the numerical summaries and parameter estimates do not provide easy ways to show how those variables are related.

This workshop provides a brief introduction to graphical methods which are useful for understanding the pattern of association among categorical variables. These methods can be helpful for both data exploration and for communicating results to others. Some of the methods described include:

- methods for discrete frequency distributions,
- association plots for two-way tables,
- mosaic displays,
- effects plots for log-linear models and logistic regression, and
- correspondence analysis.
- models for repeated measures

This course is an updated version of Graphical Methods for Categorical Data, with somewhat greater introductory material on logistic regression and loglinear models. Categorical Data Analysis Using the SAS(R) System by Stokes, Davis, and Koch (SAS Institute, 1995, ISBN 1-55544-219-6) is a useful adjunct to the course and will be available in the York bookstore (under Math 000).