STA 2101/442: Methods of Applied
Statistics
University of Toronto,
Fall 2017
Instructor:
Jerry Brunner
Lecture Friday
2:10-5:00 in Sidney Smith 2118
Note: This page is under construction, and will be updated frequently
throughout the term.
Solutions for Quiz 11 are now posted under
Information about the final exam
Information about the final exam is available here.
- Course Outline
- Formula Sheet
- Computing Resources: Information and Links.
- Assignments
- Assignment One (Mostly review): Quiz on Friday Sept. 15th. Bring a calculator.
- Assignment Two: Quiz on Friday Sept. 22nd. Cancelled
- Assignment Three: Quiz on Friday Sept. 29th. Please see
Fixes for the math data.
- Assignment Four: Quiz on Friday Oct. 6th.
- Assignment Five: Quiz on Friday Oct. 13th.
- Assignment Six: Quiz on Friday Oct. 20th.
- Assignment Seven: Quiz on Friday Oct. 27th.
- Assignment Eight: Quiz on Friday Nov. 3d.
- Assignment Nine: Quiz on Friday Nov. 17th.
- Assignment Ten: Quiz on Friday Nov. 24th.
- Assignment Eleven: Quiz on Friday Dec. 1st.
- Lecture Overheads
- Introduction to R
- Statistical Introduction: Applied regression
- Analysis of the SENIC data with R
- Large-sample tools
- Introduction to SAS (Optional for STA442)
- Analysis of the SENIC data with SAS (Optional for STA442)
- Random Vectors
- Some large-sample tests
- Likelihood Part One
- Likelihood Part Two: Wald tests
- Wald tests with R
- Logistic Regression
- Logistic Regression with R
- Poisson Regression
- Poisson Regression with R
- The Zipper example
- Omitted Variables and Instrumental Variables
- Multinomial Logit Models
- Multinomial Logit Models with R
- Interactions and Factorial ANOVA
- Interactions with R
- Factorial ANOVA with R
- Within cases for normal data
- Normal within cases with R
- Within cases for binary data
- Binary within cases with R
- The Bootstrap
- Textbooks: The texts are mostly for background reading in case you need some review, or you want to go beyond what is covered in lecture. They are available in PDF format free of charge.
-
Linear models with R (2009) by J. Faraway.
- Linear models in statistics
(2008) by A. C. Renscher and B. G. Schaalje. A strong masters level regression text with a
good linear algebra review.
- Statistical
models (2003) by A. C. Davison. This is the place to look if you want
the real truth about almost any applied statistical topic.
-
Introduction to R by Venables, Smith and
others. This free 100 page document is very helpful if you
plan to do serious work with R.
All course materials prepared by Jerry are licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. Source code is available above.