STA 2212H: Mathematical Statistics II

January 9 to April 2 2024
Tuesday 10.10 am - 1.00 pm Eastern

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Office Hours

Monday 7.00--8.00 pm (Zoom), and
Tuesday 4.00--5.00 pm (Hydro 9124)

Teaching Assistant

Junhao Zhu

Week 12 April 2

Week 11 March 26

Week 10 March 19

  • Slides
  • Slides with scribbles
  • Link to Peng Ding's course notes from his Causal Inference course at UC Berkeley
  • Link to Hernan and Robins book What If?

Week 9 March 12

Week 8 March 5

Week 7 February 27

Week 6 February 13

  • Slides
  • Slides with scribbles
  • PNAS paper on active learning
  • Testing in All of Statistics is in Chapter 10; if you're reading the modules, it's pages 151--175 and 176-200.

Week 5 February 6

Week 4 January 30

Week 3 January 23

Week 2 January 16

Week 1 January 9

Course Information

Syllabus

Texts

  • Required
  • 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.