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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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