STA 2212H: Mathematical Statistics II

January 10 to April 4 2023
Tuesday 10.10 am - 1.00 pm Eastern
OISE 5150

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Office Hours

Mondays 7.00 -- 8.00 pm (Zoom), Tuesdays 4.00--5.00 pm (Hydro 9124)

Week 12 April 4

• Slides

Week 11 March 28

• Slides
• Slides (with scribbles)
• Grad tips from Daniela Witten
• Imposters Anonymous also by DW
• As a student, you can join the Institute of Mathematical Statistics for free!

Week 10 March 21

• Slides
• Slides (with scribbles)

Week 9 March 14

• Slides
• Slides (with scribbles)
• Syllabus final update
• Some articles on quantile regression:
  • Koenker and Hallock, 2001, a gentle introduction
  • Koenker, 2017 a review paper
  • R package quantreg

March 7 Updated Syllabus

• Several possible topics are listed for March 14, 21, 28; please let me know what you'd like to see covered

Week 8 March 7

• Slides
• Slides (with scribbles)

Week 7 February 28

• Slides
• Slides (with scribbles)
• Paper on social media use
• HW 7 paper on septic shock

Week 6 February 14

• Slides
• Slides (with scribbles)

Week 5 February 7

• Slides (Updated Feb 7 am)
• Slides (with scribbles)

Week 4 January 31

• Slides
• Slides (with scribbles)

Week 3 January 24

• Slides
• Slides (with scribbles)
• Report from Canadian Centre for Substance Use and Addiction

Week 2 January 17

• Slides
• Slides (with scribbles)
• Science article
• Supplement

Week 1 January 10

• Notes on likelihood inference
• Slides
• Slides (with scribbles)

Course Information Sheet

Syllabus

We will use Piazza for discussion, you will find an entry for Piazza in the course menu. If you click it, you will be asked to sign up. Please see the instructions in the handout, especially the highlighted bits.

Texts

• Required
  • Mathematical Statistics by K. Knight; Cambridge University Press
    Hard copy available at publisher's website
  • All of Statistics by L. Wasserman. e-copy here or see course page on Quercus
  • Statistical Models by A.C. Davison.
• For reference
  • Computer Age Statistical Inference by B. Efron and T. Hastie
  • Statistical Inference by G. Casella and R.L. Berger

Computing

I will always refer to the R computing package and I highly recommend the RStudio environment. You will need to install both of these on your laptop. I am using Version 4.1.1 of R, and Version 1.4.1717 of Rstudio. You can download R from https://cran.r-project.org/ and the free Desktop Version of Rstudio from https://rstudio.com/products/rstudio/\#rstudio-desktop.

I also strongly recommend using R Markdown to prepare your homework, but you can use LateX or Word if you must. For questions involving computing you will need to submit working code. This is easy in R Markdown, but R scripts will also be accepted. Neat homework makes it easier on the grader, and a happy grader is a generous grader.

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