What are they and how do you do one?
The Department of Statistical Sciences offers STA496/STA497/ST498/STA499: Readings in Statistics. This course allows high achieving statistics students to expand their knowledge in an area/to a level of depth that is usually outside what is offered in other undergraduate statistics courses.
It can be a great opportunity to test out if you like conducting research and it can help you think about whether you’re interested in graduate level studies. It is also a good way to get a high quality reference letter (assuming things go well) for graduate school.
Independent study under the direction of a faculty member. Students wishing to take this course must have the permission of the Department of Statistical Sciences and of the prospective supervisor. Not eligible for CR/NCR option.
At least 1.0 FCE 300+ level STA courses with a minimum grade of 80% in each course.
First and foremost, here are some key things to know about my personal policies for reading courses:
There are two styles of reading course you could consider:
You propose a topic for which data is available that you wish to apply statistical methods to and produce a report. This style of project may be useful if you’re considering a thesis-based Master’s in an applied statistics area as it lets you dip your toe in and see if you like it.
I tend to be most interested in topics on social and economic issues, but part of the reason I am a Statistician is because I love learning new things. Convince me your topic is interesting and/or relevant to making the world a better place and if I have the right skills to support you, I’ll be interested.
I do not use a lot of Bayesian, machine learning or time series methods in my own work, and personally use R. Topics using these methods or other programming languages aren’t necessarily ruled out, but you’ll need to demonstrate a plan for reasonable pre-/co-requisite courses and previous experience.
I am also open to co-supervising with faculty from other disciplines for cross-disciplinary work.
You choose a topic, related to one of my interest areas below, and together we create a reading and task list for your to work through across the year. You might write a literature review, prepare a workshop or talk, write blog posts, etc. This is more similar to a traditional course experience than option 1, but is an opportunity to explore a topic not covered in other statistics course, build professional skills relevant to research/future employment.
ethical professional practice for statisticians
indigenous data sovereignty
ethics of web scraping
graphicacy and how not to lie with charts
sampler platter of ethics topics, e.g. algorithmic bias, disclosure risk, privacy/confidenitality, accessibility, reproducibility, professional codes of conduct
statistics education
assessment practices for ethical professional practice
teaching and learning simulation-based inference
trauma-informed pedagogy for statistics classrooms
online learning (potential data from STA130)
I may consider some other topics, but the above are best aligned with my current research.
See the information on the Special Enrolment Sharepoint Page for the Department. Note: Applications have closed for the 2021–22 year.
Syllabus: Draft as of 2021-09-20
Meet my students: Zhixing Hong , David Pham , Qihui Huang
The plan is be to have ~6 meetings each semester, so equivalent to having 12 classes for a normal single-semester, half-credit course. No meetings planned during the final assessment periods.
September 15: Introductions and discussion of goals and syllabus
Homework tasks:
(Re-)Read at least ONE of:
Read and take notes on (it is okay to skim/not understand everything!) at least ONE of:
Ethics in statistical practice and communication: Five recommendations by Andrew GelmanOR
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 by Bender, Gebru, McMillian-Major and Shmargaret Shmitchell (who is definitely not Margaret Mitchell, whom Google also fired), (~60 minutes) (You might also like this video reading group, but totally optional. Please also don’t take this as ‘being ethical gets you fired from Google’, as I think this is more just a notable bump along the way as organizations do try to improve, or at the very least to limit their liability!) OR
Another reading you propose to me by 11:59 a.m. ET this Friday.
Based on these readings, and your own knowledge and interests, do a brainstorm (~15–20 minutes) and then organize it into a mind map (~15–20 minutes) of concepts in ethical practice for statisticians. Bring it to the next meeting, prepared to chat through it.
September 29: Confirm syllabus; Discuss readings and mind maps/brainstorms; Confirm individual topics; Annotated bibliographies
October 13: My example seminar on graphicacy (or other topic TBD)
October 27: Wrap-up from seminar; Bring a reading from your annotated bibliography and present the key points to the group; Mid-year presentation expectations
Reading week, no meetings
November 17: Writing tips; Annotated bibliography check-in; Midyear presentation check-in
December 1: Mid-year presentations (another date may be organized for presentations, by agreement. If so, this meeting could be replaced by it or used as practice.)
January 11: Research progress check, annotated bibliography feedback (1-1 meetings)
January 25: Student seminar 1
February 8: Student Seminar 2
March 1: Student Seminar 3
March 15: Research progress check (1-1 meetings)
March 29: Final presentation (Another date may be organized for presentations, by agreement. If so, this meeting could be replaced by it or used as practice.)
Title: And the nominees are…An empirical study of the effects of a Tony Award Win and Nomination on a Show’s Success
You can hear Sam discuss the results of her project and her experience undertaking a reading course in her invited talk at the Toronto Data Workshop in May 2021.
Follow Sam on Twitter, @WhamBamGAM.
Title: How do consumer attitudes and behaviours change in the light of current events? A comparison of notable events in the United States, 2000–2009
Prof. Rohan Alexander has written up two of the reading courses he’s offered and provided the details on his website.