Tutorials Friday 10:10-11:00 and 12:10-1:00 in Room 2060, Deerfield Hall.
Note: This page is under construction, and will be updated frequently throughout the term.
Remember, the main hint about the final exam is that it will be like the homework problems. The homework problems tell you what you should be able to do. The lectures are to show you how to do the problems, and the text is a source of raw materials for the lectures.
Jerry's office hours for the final exam:
- Thursday Dec. 4th, 10:10-11:30
- Tuesday Dec. 9th, 12:10-2:00
- Thursday Dec. 11th, 12:10-2:00
2013 Final Exam: PDF View LaTeX Download LaTeX
Quiz solutions (except for the R code)
Full textbook: Renscher and Schaalje's Linear models in statistics may be downloaded here.
- Syllabus
- Formula Sheet
- Current Formula Sheet: PDF View LaTeX Download LaTeX
- 2013 Final Formula Sheet: PDF View LaTeX Download LaTeX
- Computing Resources: Information and Links.
- Assignments
- Assignment One (Mostly review): Quiz on Friday Sept. 19th
- Assignment Two: Quiz on Friday Sept. 26th
- Assignment Three: Quiz on Friday Oct. 3d
- Assignment Four: Quiz on Friday Oct. 10th
- Assignment Five: Quiz on Friday Oct. 17th
- Assignment Six: Quiz on Friday Oct. 24th
- Assignment Seven: Quiz on Friday Oct. 31st
- Assignment Eight: Quiz on Friday Nov. 7th
- Assignment Nine: Quiz on Friday Nov. 14th
- Assignment Ten: Quiz on Tuesday Nov. 25th in lecture
- Assignment Eleven: Quiz on Friday Nov. 28th
- Lectures Parts of the lectures are on overheads; the rest will be hand-written on the board.
- Statistical introduction. See Chapter One of Linear models in statistics for another introduction.
- Moment-generating functions: See your STA256 or 257 text.
- Introduction to R: See Appendix B of Linear models with R.
- More linear algebra: See Chapter 2 of Linear models in statistics for more detail.
- Random vectors: See Chapter 3 of Linear models in statistics for more detail.
- Linear model and least squares: Handwritten on board. PDF is incomplete but possibly better than nothing.
- Least squares with R
- Multivariate normal See Chapter 4 of Linear models in statistics for more detail.
- Inference for the normal linear model Part One: Handwritten on board.
- PDF: Some parts were done a little better in class.
- Inference with R: Part One
- Prediction intervals: Handwritten on board.
- Prediction intervals with R
- General linear test: Handwritten on board.
- General linear test with R
- The centered model: Handwritten on board.
- The centered model with R
- Residual diagnostics: Handwritten on board.
- PDF: This is not exactly what I did in class, but it's close most of the time.
- Residual diagnostics with R
- Polynomial regression and weighted least squares: Handwritten on board.
- Breaking rocks with R
- Categorical independent variables and interactions
- Categorical independent variables and interactions with R
- Random independent variables
- Omitted independent variables
- Modeling non-zero covariance between X and ε
- PDF (Including handwritten) OpenOffice.org format
- Automatic variable selection
- Logistic regression
- Logistic regression with R
- Stepwise logistic regression with R
- Data sets from lectures and homework
- R function for the general linear test. It's okay to use this on homework assignments.
All course materials prepared by Jerry are licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. Source code is available. See the link above for more information.