

Course ID:  BIOS 8110. 3 hours. 
Course Title:  Categorical Data Analysis 
Course Description:  Introduction to analysis of categorical data including log
linear models, logistic regression, probit models, graphical
models and casual inference. Motivating examples will be drawn
directly from the literature in the health, biological,
medical, and social sciences. 
Oasis Title:  CATEGORICAL DATA 
Prerequisite:  BIOS 7010 or STAT 6210 or STAT 6310 
Semester Course Offered:  Offered fall semester every year. 
Grading System:  AF (Traditional) 

Course Objectives:  At the end of the course, the successful student should be able
to do the following:
1. Modeling and inference for contingency table using log
linear models;
2. Using graphical models and related ideas to organize log
linear modeling;
3. Perform logistic regression analyses with multiple
predictors;
4. Compare different models with respect to their predictive
power;
5. Use graphical and other methods for assessing the adequacy
of the fitted model;
6. Interpret each coefficient in the model;
7. Describe the methods and results to a nonstatistical reader. 
Topical Outline:  Analysis of contingency tables; loglinear models; logistic
regression; probit model; Goodnessoffit tests; model
selection; zeroinflated counts; graphical models; causal
inference 