BIOS 6331: Regression Analysis in Biostatistics

This course introduces the methods for analyzing biomedical and health related data using linear regression models. The course will introduce the student to some basic theories in linear models but would mainly focus on applied linear model fitting, regression parameter estimation and hypothesis testing. The course will involve model selection, diagnosis and remedial techniques to correct for assumption violations. The students will learn how to apply SAS procedures PROC REG, PROC CORR, and PROC GLM and interpret the results of analysis. Emphasis will also be placed on the development of critical thinking skills

BIOS/PUBH 6541 - Biostatistics

This 4 credit course examines statistics in public health and related sciences, including sampling, probability, basic discrete and continuous distributions, descriptive statistics, hypothesis testing, confidence intervals, categorical data analysis, regression, and correlation. Emphasis will be on the development of critical thinking skills and health data analysis applications with computer software

BIOS 9136 - General and Generalized Linear Models

This course provides students with the theories of the classical linear model and the general linear model for continuous outcome and linear relations, then the Generalized Linear Model for nonlinear relations and discrete outcomes. The first half of the course includes theories of the linear regression model with the matrix algebra and multivariate normal distribution, then to the analysis of quadratic forms and the study of the General Linear Model. The second half of the course begins with an introduction of the components of a Generalized Linear Model and methods of fitting these models. It also covers the most widely used types of models, such as logistic regression and log-linear models

BIOS 6331: Regression Analysis in Biostatistics

This course introduces the methods for analyzing biomedical and health related data using linear regression models. The course will introduce the student to matrix algebra as used in linear models. The course will involve model selection, diagnosis and remedial techniques to correct for assumption violations. The students will learn how to apply SAS procedures PROC REG, PROC CORR, and PROC GLM, etc and interpret the results of analysis. Emphasis will also be placed on the development of critical thinking skills