Surveys, Sampling, and Observational Data

STA304 is an upper-level undergraduate course at the University of Toronto’s Department of Statistical Sciences.

9 September 2020: As we kick off a term that will be difficult for us all, a special message from my fellow Australian Chris Hemsworth: https://twitter.com/netflix/status/1302008281909661696

Syllabus

Course syllabus

Assessment

Item Weight (%) Due date
Problem Set 1 10 27 September 2020
Problem Set 2 15 7 October 2020
Problem Set 3 15 16 October 2020
Problem Set 4 20 2 November 2020
Test 10 19 November 2020
Final Report 30 During Final Assessment Period

Content

Week 1

10 September 2020, Establishing a foundation

This week I’ll upload a few videos before-hand, to save us some time, but we’ll also meet on Thursday morning to discuss a few aspects, meet the TAs, answer any of your questions, and run through some examples. A recording of that will be uploaded. I will run the lab (11am-noon), which will just focus on dealing with any installation issues. As that’s more specific to individuals I won’t record that.

The core of the course is in the notes that I will provide links to. You should go through these in detail. Run the examples. Try to change them slightly and see what happens. Do the readings that you are interested in. Read the help docs for the functions. This is the core of your learning. Lectures mostly just exist for you to have a chance to discuss your thoughts with me.

Read & write - that is the life that you have signed up for. When it comes to this course, if you are not reading or writing, then you are almost surely wasting your time.

This week is about ensuring that you have an appropriate foundation on which we can build the rest of the course. You should already have covered much of this week’s content in previous courses - this week ensures that everyone has covered the basics. If you have gaps in your knowledge, then please address them.

Notes

Lecture

  1. Instructor introduction and course overview - pre-recorded.
  2. TA introductions.
  3. Take a survey and criticize survey in break-out rooms.
  4. One person in each team to present pros/cons/interesting.
  5. Break.
  6. R Studio Cloud - recorded.
  7. cesR - recorded.
  8. R Markdown - recorded.
  9. Then you try and we deal with installation issues.

Readings

Toronto Data Workshop