STA2101: Methods of Applied Statistics I

and

STA442: Methods of Applied Statistics

University of Toronto, Fall 2011

Lecture Friday 2:10-5:00 p.m. Ramsay Wright 117

Office Hours Wednesday 11-1 and Friday 10-11 in SS6025

This page is under construction, and will be updated frequently throughout the course.

Office Hours Monday Dec 12th: 10am - noon.

Information about the final exam, including one last computer assignment.

If you are getting strange data errors trying to read data you've found online, check and see if the problem is with the last variable you're trying to read. If so, SAS for unix is probably choking on DOS/Windows line breaks. These are invisible characters that signal the end of a line, and they are not the same for the 2 operating systems. Say the data are called something like lifetime.data. Try something like this:

      bash-3.00$ dos2unix < lifetime.data > deathtime.data

• Course Outline
• Term Paper for STA2101: No paper is required for STA442
• Computing information and links
• Homework Assignments
  1. Assignment 1: Do these matrix algebra review questions in preparation for Quiz 1 on Friday Sept. 23d. If you don't have a linear algebra textbook handy, see Section A2 in Appendix A.
  2. Assignment 2: Do these questions in preparation for Quiz 2 on Friday Sept. 30th. Bring the R parts to the quiz; they may (or may not) be handed in.
  3. Assignment 3: Do these questions in preparation for Quiz 3 on Friday Oct. 7th. Bring the R parts to the quiz; they may (or may not) be handed in.
  4. Assignment 4: Do these questions in preparation for Quiz 4 on Friday Oct. 14th. Bring the R parts to the quiz; they may (or may not) be handed in.
  5. Assignment 5: Do these questions in preparation for Quiz 5 on Friday Oct. 21st. Bring the R parts to the quiz; they may (or may not) be handed in.
  6. Assignment 6: Do these questions in preparation for Quiz 6 on Friday Oct. 28th. Bring the R parts to the quiz; they may (or may not) be handed in.
  7. Assignment 7: Do these questions in preparation for Quiz 7 on Friday Nov. 4th. Bring the R parts to the quiz; they may (or may not) be handed in.
  8. Assignment 8: Do these questions in preparation for Quiz 8 on Friday Nov. 11th. Bring the R parts to the quiz; they may (or may not) be handed in.
  9. Assignment 9: Do these questions in preparation for Quiz 9 on Friday Nov. 18th. Bring your SAS log and list files to class. You know they'll probably be handed in.
  10. Assignment 10: Do these questions in preparation for Quiz 10 on Friday Nov. 25th. Bring your SAS log and list files to class. They may be handed in.
  11. Assignment 11: Do these questions in preparation for Quiz 11 on Friday Dec. 2nd. Bring your SAS log and list files to class. They may be handed in.
• Handouts and Overheads: You may want to print these and bring to class so you can write notes on them.
  1. Introduction to R
  2. Large sample tools
  3. Random vectors and the multivariate normal
  4. Maximum Likelihood
  5. Wald (and Score) Tests
  6. Likelihood with R, Part One
  7. Distribution-free Wald-like tests
  8. Linear Regression Part 1
  9. Analysis of Residuals
  10. Regression on the Trees data
  11. Linear Regression Part 2: Categorical independent variables and a bit about multiple comparisons (revised).
  12. Analysis of the (little) tubes data
  13. Some unix and emacs commands. You might as well print this handout and keep it with you while you work, at first.
  14. Brief Introduction to SAS
  15. Little Tube data with SAS: Data definition, Contrasts, multiple comparisons, custom hypothesis tests with proc glm and proc reg.
  16. SENIC data with SAS Part One: Read and describe the data, elementary tests
  17. Read and Check the Math data with SAS, including how to read character data.
  18. Introduction to Logistic Regression (Updated)
  19. Birth weight data: Logistic regression with R
  20. Birth weight with SAS: Part 1 (Data Description)
  21. Birth weight with SAS: Part 2 (Logistic Regression)
  22. Birth weight with SAS: Part 3 (More Logistic Regression)
  23. Stepwise Logistic Regression on the birth weight data with R
  24. Birth weight with SAS: Part 4 (Yet more Logistic Regression). This is for reference, and will not be covered in class.
  25. Factorial ANOVA: An elementary discussion.
  26. Factorial ANOVA with SAS proc glm and proc reg.
  27. Within Cases Part One: The humble matched t-test
  28. Within Cases Part Two: Hotelling's t² with R (The Multivariate t-test)
  29. Within Cases Part Three: Multivariate Linear Model
  30. Within Cases Part Four: Multivariate Tests on Within-cases data
  31. Within Cases Part Five : The Covariance Structure Approach
  32. Within Cases Part Six: SAS Examples
• Readings and resources: These are substitutes for a printed textbook.
  • library.nu: If you register on this site, it will be easy to download free textbooks including the following:
    • Statistical models by A. C. Davison: A strong, high-level book. If you want to know exactly what is going on with most applied statistical topics, this is a good place to look.
    • Applied linear statistical models (5th ed) by Kutner, Nachtsheim, Neter and Li: This books give a simple and thorough explanation of many standard topics in univariate linear models and experimental design.
    • A course in large sample theory by T. Ferguson: More than you need for this course, but a gem.
    • Applied Statistics and the SAS Programming Language by Ronald P. Cody and Jeffrey K. Smith.
    • Modern Applied Statistics with S (4th ed.) by W.N. Venables and B.D. Ripley. This includes R.
  • Introduction to R: A very nice 100-page PDF document. Highly recommended if you are going to be using R for serious work.
  • Appendix A from the text for another course. It has review material and some material from the beginning of the course. This is work in progress but it still may be useful.
  • Introduction to SAS and unix
  • SAS manuals: You probably want SAS/STAT
• Data sets used in homework and lectures