Unique numbers: 59195 (M374G), 59310 (M384G), and 57300 (CAM384T)
Time: MWF 10:00 -11:00
Room: RLM 6.116
Brief description: Simple and multiple linear regression, inference in regression, prediction of new observations, diagnostics and remedial measures (including transforming nonlinear data to apply linear models), model building (including interaction terms and indicator variables), and other topics in regression analysis as time permits. Emphasis will be on both understanding the theory and using that understanding to apply the theory to analyze real data. Students will use Arc regression software (downloadable from the Web on various platforms) to analyze data.
Prerequisite: Undergraduate courses in probability and statistics, such as M362K plus either M378K or M358K. Some experience with using matrices (an undergraduate linear algebra course should be more than adequate) is also desirable. Permission of instructor is required for M374G.Textbook: Cook and Weisberg, Applied Regression Including Computing and Graphics, Wiley, 1999. The course will cover most of Chapters 1 - 15 of the text, plus some supplementary material in the early chapters.