STAT 335: Generalized Linear Models

نماذج خطية معممة
STAT 335: Generalized Linear Models
Prerequisite Course: STAT 332 (Regression Analysis)
Concurrent Requirement Course: STAT 337 (Design and analysis of experiments)
Course Description:
1. Review: some matrix algebra, some important distributions, quadratics forms, some statistical inferences methods (estimation, hypotheses testing), model fitting and some principles of statistical modeling, simple linear regression, comparing the means of two groups.
2. Exponential family and generalized linear models.
3. Sampling distribution for score statistics
4. Sampling distribution for the deviance.
5. Normal Linear Models.
6. Binary Variables and logistic Regression.
7. Nominal and ordinal logistic Regression.
8. Poisson Regression and log-linear models.
9. Clustered and Longitudinal Data
Course Main Objectives:
To introduce the theoretical and applied concepts and principles of generalized linear models to the students. This will help them in how to select the appropriate model and how to analyze the data.