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 Faculty of Arts
 Faculty of Pure and Applied Science

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AS/SC/AK/ MATH 3034 3.0 W

Applied Categorical Data Analysis

      Regression using categorical explanatory variables, one-way and two-way analysis of variance. Categorical response data, two-way and three-way contingency tables, odds ratios, tests of independence, partial association. Generalized linear models. Logistic regression. Loglinear models for contingency tables. Note: Computer/Internet use may be required to facilitate course work.
      This course is a continuation of MATH 3033 3.0, Classical Regression Analysis, or of MATH 3330 3.0, Regression Analysis. The focus of the course is on the analysis of categorical data, including regression using categorical explanatory variables, contingency table, logistic regression, log-linear regression and generalised linear models.
      Students will use statistical software packages, either SPLUS or SAS, for data analysis.
      The text is A. Agresti, An Introduction to Categorical Data Analysis (Wiley).
      The final grade will be based on assignments, term tests, a project and a final examination.

Prerequisite:AS/SC/MATH 3033 3.0 or AS/SC/AK/MATH 3330 3.0.
Exclusion:Not open to any student who has passed or is taking AS/SC/MATH 4130G 3.0.

Coordinator: P. Song

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