STA 441: Methods of Applied Statistics
University of Toronto Mississauga,
Winter/Spring 2018
Instructor:
Jerry Brunner
Lectures Monday 11:10-1:00 and Wednesday
11:10-12:00 in IB 235
Tutorials Tuesday 10:10-11:00 in DH 2080 and 11:10-12:00 in DH 2070
Monday office hours will be in IB140.
Note: This page is under construction, and will be updated frequently
throughout the term.
Information about the final exam
Jerry's office hours will be Wednesday the 11th, Friday the 13th and Monday the 16th from 11-1 in DH-4001.
Asal's office hours will be Thursday April 12th from 10-12.
- Course Outline
- SAS OnDemand: Run SAS for free online.
- Computing Resources: Information and Links
- Formula Sheet
PDF
View LaTeX
Download LaTeX
- Assignments: Solutions are not available. Think about the questions.
- Assignment
1: Quiz on Tuesday January 16th.
- Assignment
2: Quiz on Tuesday January 23d.
- Assignment
3: Quiz on Tuesday January 30th.
- Assignment
4: Quiz on Tuesday February 6th.
- Assignment
5: Quiz on Tuesday February 13th.
- Assignment
6: Quiz on Tuesday February 27th.
- Assignment
7: Quiz on Tuesday March 6th.
- Assignment
8: Quiz on Tuesday March 13th.
- Assignment
9: Quiz on Tuesday March 20th.
- Assignment
10: Quiz on Tuesday March 27th.
- Assignment
11: Quiz on Tuesday April 3d.
- Lecture Overheads Some of these present concepts, and some show SAS input and output. You might want to print the SAS programs and bring them to class so you can write notes on them during lecture.
- Introduction to data analysis: See Chapter 1.
- Introduction to SAS: See Chapter 2.
- SAS Example One: Basic descriptive statistics
on the cars data. See Chapter 2.
- Multiple regression (mostly review): See Chapter 5.
- SAS Example Two: Regression on the cars data.
See Chapter 5.
- SAS Example Three: The math data.
See Chapters 2 and 5.
- Logistic Regression Concepts: See Chapter 6.
- SAS Example Four: Logistic regression on the
math data, Part One.
- SAS Example Five: Logistic regression on the
math data, Part Two.
- The multinomial logit model: Logistic regression with more than 2 categories
- SAS Example Six: Multinomial logit on the math data
- One-way ANOVA with multiple comparisons: Concepts. See Chapter 3.
- SAS Example Seven: One-way ANOVA with multiple comparisons on the scab disease data. Also a quick ANCOVA on the cars data.
- Permutation and Randomization tests
- SAS Example Eight: Randomization tests on the scab disease data.
- Factorial analysis of variance: See Chapter 7.
- SAS Example Nine: Factorial ANOVA on the rotten potato data.
- Multivariate analysis of variance. See Chapter 9.
- SAS Example Ten: Multivariate analysis of the little tubes data.
- Within cases Part One. See Chapter 9.
- SAS Example set Eleven: Multivariate approach to within cases
- Within cases Part Two. See Chapter 9.
- SAS Example set Twelve: Covariance structure approach to within cases
- Within-cases for binary responses.
- SAS Example set Thirteen: Within-cases for binary responses with proc nlmixed.
- Textbook
- Chapter 1: Vocabulary and basic concepts used throughout the course, and also a brief discussion of elementary significance tests.
- Chapter 2: Introduction to SAS. The unix/linux details do not apply to this class.
- Chapter 3: Comparing several means.
- Chapter 4: Simple categorical data analysis of the Berkeley graduate admissions data
- Chapter 5: Multiple regression
- Chapter 6: Logistic regression
- Chapter 7: Factorial analysis of variance
- Chapter 8: Selecting sample size
- Chapter 9: Multivariate and within-cases
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- Home page for the textbook. This has the current version of the full book. You are responsible for the individual chapters posted above. The current version of the full book (both before and after where we are in the class) may change without notice. If you are interested, the best time to obtain a copy of the full text will be when the term is over. Feel free to take a look at any time to see how it's going.
- SAS programs from lecture
All course materials prepared by Jerry are licensed under a Creative Commons Attribution-ShareAlike 3.0 (or later) Unported License.