BST681 - LINEAR REGRESSION

College of Public Health

Credits: 3

BST 681, the first in a two-semester sequence in regression modeling, covers linear regression models for normally distributed outcomes. The course will cover simple and multiple linear regression, estimation, interpretation, hypothesis testing, model building and diagnostics, matrix algebra for regression, and an introduction to design of experiments. The course will include the use of computing tools to apply these models to real data.

Prerequisite(s):
Prereq: BST 600 or consent of instructor.