Tutorials Thursday 5:10-6:00 in Room 2072, Davis Hall.
Note: This page is under construction, and will be updated frequently throughout the term.
Term tests with solutions are posted below.
Solution to Assignment 9, Question 1: I got mixed up in office hours. As you can see, it's simple if you approach it correctly.
Quizzes with solutions are posted below, including Quiz 11.
Old exams from 2013 and 2014 are posted below.
Assignment 12 is posted below. This material may or may not be on the final exam.
The last formula sheet is posted below. This is what you will get with the final exam. Definitely use it to study.
Final Exam
- The final exam is on Friday Dec. 11th from 5-8pm in IB120.
- It starts like this:
- The R part of the regular exam (not the special deferred exam) will use The Pig Weight data. You will answer questions based on my output. Here is some background about the data set:
Pigs are routinely given large doses of antibiotics even when they show no signs of illness, to protect their health under unsanitary conditions. Pigs were randomly assigned to one of three antibiotics. Dressed weight (weight of the pig after slaughter and removal of head, intestines and skin) was the dependent variable. Additional independent variables are mother's and father's live adult weight.
- Jerry's Office hours. These will be in DH3050 if I can reserve the room.
- Thurs Dec. 3, 12-2 (Jerry)
- Tuesday Dec. 8th 11-1 (Jerry)
- Wed. Dec. 9th 12:30-2 (Jerry)
- Thurs. Dec. 10th 11-1 (Jerry)
- Fri December 11th 2-4 (Eman)
- Test and quiz solutions will be posted shortly. Once they are posted, there will no more discussion of the marking. There will be an additional short interval before the Quiz 11 solution is posted.
- The best way to study is to re-do the homework. Details were provided in lecture on Thursday November 26th.
- Here are some old exams. It may look like all the questions are straight from homework, but I do use old exams as a source of fresh homework problems, so some of them were new.
- Quizzes with solutions (but no R code)
- Term tests with solutions
Textbook: Renscher and Schaalje's Linear models in statistics is available free in pdf format through the U of T library one chapter at a time. A full copy may also be downloaded here.
- Syllabus
- Computing Resources: Information and Links.
- Formula Sheet
- Current Formula Sheet: PDF View LaTeX Download LaTeX
- Assignments
- Assignment One (all review): Quiz on Thursday Sept. 17th in tutorial.
- Assignment Two: Quiz on Thursday Sept. 24th in tutorial.
- Assignment Three: Quiz on Thursday Oct. 1st in tutorial.
- Assignment Four: Quiz on Thursday Oct. 8th in tutorial.
- Assignment Five: Quiz on Thursday Oct. 15th in tutorial.
- Assignment Six: Quiz on Thursday Oct. 22nd in tutorial.
- Assignment Seven: Quiz on Thursday Oct. 29th in tutorial.
- Assignment Eight: Quiz on Thursday Nov. 5th in tutorial.
- Assignment Nine: Quiz on Thursday Nov. 12th in tutorial.
- Assignment Ten: Quiz on Thursday Nov. 19th in tutorial.
- Assignment Eleven: Quiz on Thursday Nov. 26th in tutorial.
- Assignment Twelve: This material may or may not be on the final exam.
- 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.
- Introduction to R: See Appendix B of Linear models with R for another introduction.
- Moment-generating functions: See your STA256 text.
- More linear algebra. See Chapter Two of Linear models in statistics for more detail. Please notice the slide entitled "Three mistakes that will get you a zero."
- Random Vectors: See Chapter Three of Linear models in statistics for more detail.
- Simple Regression: Handwritten on the board. See Chapter 6 in the text.
- Multiple Regression Part One: Estimation. Handwritten on the board. See Chapter 7 in the text. Here is a cleaner proof of the Gauss-Markov Theorem.
- Least squares with R
- Joint moment-generating functions and the multivariate normal.
- Inference Part One: Handwritten on board
- Interpretation of regression coefficients
- Inference with R: Part One
- Prediction intervals: Handwritten on board
- Prediction intervals with R
- Categorical independent variables
- Categorical independent variables with R
- General linear test and Full-reduced: Handwritten on board
- General linear test and Full-reduced with R
- PDF OpenOffice.org format
- R function for the general linear test. It's okay to use this on homework assignments. Access it with source.
- Regression Diagnostics: Handwritten on board
- Regression Diagnostics with R
- Random Independent Variables
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.