Course: STAT 22400=PBHS 32400
Title: Applied Regression Analysis
Instructor(s): James Dignam
Teaching Assistant(s): Vasileios Katsianos, Zhan Lin
Class Schedule: Sec 01: TR 11:20 AM-12:40 PM in TBA
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.
Prerequisites: STAT 22000 or 23400 with a grade of at least C+, or STAT 22200 or 22600 or 24500 or 24510 or PBHS 32100, or AP Statistics credit for STAT 22000. Also two quarters of calculus (MATH 13200 or 15200 or 15300 or 16200 or 16210 or 15910 or 19520 or 19620 or 20250 or 20300 or 20310).
