STAT 3301: Regression and Statistical Computing
Instructor. Aaron J. Molstad (amolstad@umn.edu)
Office hours. Monday 4:00 – 5:00PM, Wednesday 9:45 - 10:45AM in Ford Hall 384
Teaching assistant. He Zhou (zhou1354@umn.edu)
TA Office hours. Tuesday and Thursday, 12:00 - 1:00PM in Ford Hall 495
Syllabus. [pdf]
Lecture. Monday, Wednesday, Friday at 12:20 - 1:10PM in Mechanical Enginerring 221
Lab. Wednesday at 8:00 - 8:50AM in Ford Hall 151
Download R. [CRAN]
Download RStudio. [Rstudio]
Code formatting guidelines. [Google style sheet]
R basics. [pdf]
Note that you must be logged into your UMN Canvas account to access course materials.
| Lecture | Topics | |||
| 1 (9/6) | Syllabus, review [slides][code] | |||
| 2 (9/8) | Probability functions, expected value and variance [slides][complete][code] | |||
| 3 (9/11) | Named distributions [slides][code] | |||
| L1 (9/13) | R markdown [zip] | |||
| 4 (9/13) | Normal distribution [slides][code] | |||
| 5 (9/15) | Estimators and estimates [slides][code] | |||
| 6 (9/18) | Monte Carlo methods [slides] |
Complete Lectures 1-6 [pdf][rmd]
Homework 1 (Due Thursday, September 21st at 4:59PM) [pdf][solutions][rmd]
| 7 (9/20) | Inversion method [slides][code] | |||
| 8 (9/25) | One-sample model [slides][code][msptemp] | |||
| 9 (9/27) | Confidence intervals[slides][code] | |||
| 10 (9/29) | T-test and its properties [slides][code] | |||
| 11 (10/2) | Type I error, power [slides][code] | |||
| 12 (10/4) | Estimating power with simulation [slides] |
Complete Lectures 7-8 [pdf][rmd]
Complete Lectures 9-12 [pdf][rmd]
Homework 2 (Due Friday, October 6th at 4:59PM) [pdf][solutions]
| 13 (10/6) | Introduction to regression I [slides][code] | |||
| 14 (10/9) | Introduction to regression II [slides][code] | |||
| 15 (10/11) | Linear regression and least squares [slides] | |||
| 16 (10/13) | Least squares estimator and prediction [slides] |
Complete Lectures 13-16 [pdf][rmd]
Homework 3 (Due Monday, October 23rd at 4:59PM) [pdf][solutions]
| 17 (10/16) | Multiple linear regression [slides][code] | |||
| 18 (10/20) | Regression diagnostics [slides] | |||
| 19 (10/23) | Inference in regression I[slides][code] | |||
| 20 (10/27) | Inference in regression II [slides] | |||
| 21 (10/30) | Prediction intervals, F-test [slides][code] | |||
| 22 (11/1) | F-test continued [slides] | |||
| 23 (11/3) | Testing interactions [slides] |
Complete Lectures 17-19 [pdf][rmd]
Complete Lectures 20-23 [pdf][rmd]
Homework 4 (Due Monday, November 6th at 4:59PM) [pdf][solutions]
| 24 (11/6) | Multicolinearity, R-squared [slides] | |||
| 25 (11/8) | Cross-validation[slides] | |||
| 26 (11/10) | AIC, BIC, Backwards elimination [slides] | |||
| 27 (11/13) | Quiz 2 Review [slides] |
Complete Lectures 24-26 [pdf][rmd]
Homework 5 (Due Monday, November 20th at 4:59PM) [pdf][solutions]
| 28 (11/17) | Model selection [slides] | |||
| 29 (11/20) | Ridge regression I [slides] | |||
| 30 (11/27) | Ridge regression II [slides] | |||
| 31 (11/29) | Applications of ridge regression [slides] | |||
| 32 (12/1) | Lasso I [slides] |
Complete Lectures 28-31 [pdf][rmd]
Homework 6 (Due Monday, December 4th at 4:59PM) [pdf][solutions]
| 33 (12/4) | Lasso II, Likelihood [slides] | |||
| 34 (12/6) | Logistic regression I [slides] | |||
| 35 (12/8) | Logistic regression II [slides] | |||
| 36 (12/11) | Quiz 3 Review [slides] |
Complete Lectures 32-33 [pdf][rmd]
Complete Lectures 34-35 [pdf][rmd]
Homework 7 (Due Monday, December 15th at 4:59PM) [pdf][submit]