The course "Analysis of Qualitative Data" or "Categorical Data Analysis" is an introduction to the theory and applications of statistical methods for investigating the relationships among discrete variables. The course will present methods for analyzing categorical data, standard methods for contingency tables such as odds ratios, tests of independence and various measures of association, generalized linear models for binary data and count data, logistic regression for binomial data, loglinear models for Poisson data. The statistical techniques discussed will be presented by many real examples involving both physical and social science data.

Prerequisites:

Statistics 220 or equivalent. It is expected that the students have a good understanding of basic descriptive statistics such as means, variances and expectation, of the inferential notions of estimate, confidence intervals and significance or hypothesis testing. Familiarity with one statistical package, e.g. Stata, Sas, Splus, Spss, Minitab and ability to access Web sites and to download files from the Web are required.

Texts:

Agresti, A. An introduction to Categorical Data Analysis. Wiley, 1996.

Optional Reference:
Hamilton, L. C. Statistics with Stata 5. Duxbury Press, 1998.