STA 2101H: Methods of Applied Statistics I

Wednesday September 15 to Wednesday December 8 2021
10am -- 1 pm Eastern


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Office Hours

Monday 7 - 8.30 pm; Wednesday 4 - 5.30 pm; on Zoom

Delivery

Lectures 1 and 2, September 15 and 22 are online only. From September 29 we are scheduled to meet in WI 1017 in person. The slides for the lectures will be posted, on good weeks before the scheduled course time, and on rushed weeks just after.

The first hour will usually be mainly lecture-style, with breaks for discussion, on the methods listed in the Syllabus. The second hour will be discussion of case studies, usually from current events, with statistical concepts reviewed as needed in that context. The third hour will be a discussion of computational methods and/or problems, questions about the course material and questions about the homework.

We will use Piazza for discussion, as it is now integrated with Quercus. You will find an entry for Piazza in the course menu. If you click it, you will be asked to sign up.

December 8

December 1

November 24

  • Slides (Nov 23 6.30 pm)
  • Slides (with scribbles)
  • See case-controls studies handout from November 17
  • The soccer example came via 538. The slide deck is here
  • HW Week 10 pdf Rmd

November 17

November 3

October 27

October 20

October 13

October 6

September 29

September 22

September 15

Before first lecture

Before the first class, I recommend that you
  • Read the blog post here
  • Read Chapter 2 Sections 1 - 4 of Faraway's "Linear Models with R"
  • check that you can link to to my course web page, the Quercus page, and to the reference texts (if you don't have a hard copy)
  • signup for Piazza
  • download and install R and RStudio

Required references

Background references

  • Statistical Models by A.C. Davison. (especially recommended for PhD students)
  • If Davision is a bit heavy, your undergraduate regression textbook may be helpful, or
  • Data Analysis and Graphics using R, by Maindonald and Braun
  • An Introduction to Generalized Linear Models by Dobson.

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.

There are many online resources for R and Rstudio. If you are new to R, you could look at Quick-R. Rstudio has some recommendations on their education page. For more experienced users, the Cheatsheets are invaluable.

Course Information Sheet Updated Sep 16

Syllabus Updated Sep 13