This paper presents a categorical data analysis by employing the use of the statistical programs R and the Statistics Online Computing Resource (www.SOCR.ucla.edu). While advances in software have made it simple to fit models to qualitative variables, they can sometimes be difficult to visualize and analyze because there are often no similarities between the levels of the variables. There are many approaches to overcome this difficulty. Basic concepts such as probability and linear regression can be extended to introduce a variety of methods and models for analyzing and interpreting categorical data. The plan is to present an examination of a particular dataset using SOCR to provide visualizations such as bar plots and line graphs, and R
to conduct the tests using logistic regression, multiple correspondence analysis, and hierarchical clustering.