|Course:||STAT 22400=PBHS 32400|
|Title:||Applied Regression Analysis|
|Instructor(s):||L. Brant Collins|
|Teaching Assistant(s):||Nathan Gill and Joelle Mbatchou|
|Class Schedule:||Sec 02:TR 2:00 PM–3:20 PM in Ryerson 251|
|Textbook(s):||Chatterjee, Hadi, Price, Regression Analysis By Example, 5th edition.|
|Description:||This course introduces the methods and applications of fitting and interpreting multiple regression models. The primary emphasis is on the method of least squares and its many varieties. Topics include the examination of residuals, the transformation of data, strategies and criteria for the selection of a regression equation, the use of dummy variables, tests of fit, nonlinear models, biases due to excluded variables and measurement error, and the use and interpretation of computer package regression programs. The techniques discussed are illustrated by many real examples involving data from both the natural and social sciences. Matrix notation is introduced as needed.
Prerequisite(s): STAT 22000 or 23400 or 24500 or 24510 or PBHS 32100 and two quarters of calculus.