MATH 353 - Advanced Statistical Data Analysis

Credits: (3)
Prerequisite(s): MATH 352
The course will expose the student to advanced topics in statistical data analysis. It will cover various regression analysis approaches through generalized linear models and as well as other topics. Theory, as well as fully worked-out numerical examples on data in the statistical package R, for each type of analysis will be presented. The emphasis will be on model accuracy and the interpretation of results. Selected topics from the following may be covered: Introduction to general and generalized linear regression models, Regression models for response with right-skewed distribution, Regression models for binary response, Regression models for categorical response, Regression models for count response, Regression models for proportion response, Regression models for repeated measures data, Hierarchical regression model, Survival analysis, Analysis of variance, Tools for tables of counts, Elements of experimental design, Factorial treatment arrangements and blocking designs