STA 4210 – Regression Analysis
MWF 2 – CSE E121
Instructor: Dr. Larry Winner
E-mail: firstname.lastname@example.org (I will not view any attachments)
Office: 228 Griffin/Floyd Hall
Office Hours: TBA (See class website)
Textbook: Applied Linear Statistical Models, 5th Ed. By Kutner, Nachtsheim, Neter, and Li
(aka Regression Analysis, STA 4210)
Tentative Course Schedule:
1 Introduction/Review Appendix A, B, 1.1,1.2
2 Least Squares for Simple Linear Reg 1.3-1.7
3 Inference in SLR 1.8,2.1-2.7
4 General Linear Test, Diagnostics 2.8-2.11,3.1-3.10
5 Simultaneous Inference, Etc. Exam 1 4.1-4.7
6 Matrix Approach to SLR 5.1-5.13
7 Multiple Linear Regression I 6.1-6.8
8 Multiple Linear Regression II 7.1-7.6
9 Quantitative and Qualitative Predictors 8.1-8.7
10 Model Selection/Diagnostics 9.1-9.4, 10.1-10.5
11 Diagnostics, Review, Exam 2
12 Remedial Measures, Homecoming 11.1-11.5
13 Autocorrelation in Time Series 12.1-12.5
14 Time Series, Thanksgiving
15 Nonlinear Regression, Logistic Regression 13.1-13.4, 14.1-14.5
· Exam 1 – Friday, September 19
· Exam 2 – Friday, October 24
· Exam 3 - Wednesday, December 10
Each exam will count 30%, and will contain an in-class and take-home portion. The take-home portion will be given out in the class period prior to the exam. It is your responsibility to receive this portion at that time. No make-up exams will be given. Homework projects will count for the remaining 10%. No late homework will be accepted, nor will electronic (e-mail) versions be accepted.
· Any handouts or graded assignments will be only handed out once. It is your responsibility to attend class and obtain course materials. Many handouts will be posted on the web.
· Due to onslaught of e-mail vermin, I will immediately delete any message with an attachment. Any e-mail should be text only with no HTML. E-mail messages should be kept to an absolute minimum, and only used in dire emergencies. E-mail is not a substitute for office hours or lectures.
· For each exam, you will be permitted to bring 1 3”x5” index card. Any formulas must be handwritten, not photocopied. I will provide any necessary tables.
· Keep up with the material, and you should find this to be an interesting, highly applicable course, regardless of your major. It is easy to fall behind, and then it may become overwhelming, as this course is a thorough treatment of Regression Analysis. Good Luck!
Academic Dishonesty: All members of the University Community share the responsibility to challenge and make known acts of apparent academic dishonesty. Acts of academic dishonesty will not be tolerated and will be referred to the Student Honor Council.
Academic Accommodations: If you have a documented disability and wish to discuss academic accommodations with me, please contact me as soon as possible.