3 Start here!

3.1 Introductions

Hi folks,

Welcome to STA303! We’re excited you’re joining us on this statistical voyage. I look forward to introducing myself to you in our first class on Wednesday, but for now, there is are basic introductions below for me and our Head TA Amin. Feel free to skip to How this course works, I know there is a lot to read in the module!

Looking forward to a great semester! See you in class on Wednesday.

3.1.1 Professor Liza Bolton, Instructor

Email: sta303@utoronto.ca (Put “[Prof. Bolton]” in the subject line to the email me directly)

Pronouns: she/her

Before moving (back) to Canada in 2019, I had lived more than half my life in New Zealand. (I still mention New Zealand a lot in class…) My current research areas are in statistics education and online learning, as well as health disparities across ethnic groups. I used to run a small consulting company and called myself a Data Ambassador. Why? Well, lots of people are consultants. I even did an internship in management consulting once upon a time. But it wasn’t a satisfying title for what I wanted my work with people to look like. I wanted something that focused on the communication and interpersonal side, not just high quality and appropriate analysis. People who aren’t confident in their ability to analyse their own data need a go-between, someone who can be an ambassador for their data! While I don’t do consulting any more, I love helping students build their technical and professional skills so they can go out into the world and be excellent ambassadors for data themselves.

Last movie I cried in: Kiki’s Delivery Service

Favourite food: Corn. Popped, on the cob, in a chip, Mmmmm.

Book most often given as a gift: A Matter of Fact: Talking Truth in a Post-Truth World by Jess Berentson-Shaw

3.1.2 Amin Banihashemi, Head TA

Email: sta303@utoronto.ca (Amin will often be the one responding to your emails)

Pronouns: he/him

I’m a fourth-year PhD student at the Institute of Medical Science. I have been a TA for STA130 in DoSS for the past 3 years and this is my second semester as Head TA of STA303.

My area of research is clinical Neuroscience, something I am passionate about. I analyze images of brain and eye structures in neurodegenerative diseases. I investigate possible associations of these structures with each other and with the ability to remember well and carry out goal-oriented tasks successfully. I love creating reproducible statistical analysis workflows in R. I also like audiobooks, candlelight, and apple pie (which I make myself!)

3.2 A few things to know upfront

  • R is the programming language used in this course.

  • I use and teach a lot of tidyverse, especially dplyr for data wrangling and ggplot for visualization.

  • The entire course is online until Jan 31. While some elements of the delivery of STA303 may be in person after that, the course will have a large online component regardless and all assessments will be able to be completed and submitted online.

    • If you are enrolled in an in-person tutorial, you will have an option to attend online instead.

    • Synchronous attendance is NOT required to pass this course, but being able to attend (online) synchronously at the times in the timetable may make things easier for you.

  • I cannot add students to a course, waive prerequisites or move them off a waitlist. If you or a friend have any questions of this nature, please reach out to the UG stats team (ug.statistics@utoronto.ca).

    • Waitlisted STA303 students may access course materials by filling out this form, but they will not be able to complete assessments during this time. The course is designed to accommodate this.

  • Check out my autoresponder message post for FAQs and other useful information.

3.2.1 Students joining off the waitlist

You do not have to submit any assessments you missed while on the waitlist. They are all knowledge basket assessments and you will have multiple future opportunities to make up those grades. See the Syllabus for more information.

If you have a friend on the waitlist, they can sign up to receive materials here.

3.3 How this course works

This course is organized into five two-week modules of learning + two one-week assessment-focus weeks.

All course material will be made available through this course guide and/or in Quercus.

All times listed are ‘Toronto time’, i.e. Eastern Time. Note that Daylight Savings Time begins Sunday, March 13, 2022. You may find this time converter helpful: https://www.timeanddate.com/worldclock/meeting.html

3.3.0.1 In most modules there be will be:

  • Asynchronous content released at the beginning.

  • A synchronous class on Wednesday at 10:00 a.m. ET (L0101) and 3:00 p.m. ET (L0201).

    • Both sessions will be the same, you only need to attend one.

    • You must be logged in with your U of T Zoom account (utoronto.zoom.us) to access the class.

    • Synchronous classes will be recorded. You’re expected to watch the recording if you cannot attend live. They will be posted on the course overview page.

  • A knowledge basket writing task.

    • Create phase due first Friday at 3:03 p.m. ET.

    • Assess phase due second Tuesday at 3:03 p.m. ET.

    • Reflect phase due second Friday at 3:03 p.m. ET.

  • Office hours.

    • Prof office hours will occur during the second half of the Wednesday synchronous classes, i.e. approximately 11:10–12:00 p.m ET and 4:10–5:00 p.m., in the same Zoom call.

    • TA office hours will take place during the Thursday tutorial times (12:00 p.m. and 5:00 p.m. ET) on the second Thursday of each module.

3.4 Hours expectations

While everyone has different work styles and learning needs, I want to provide some guidance around how I expect this course to look for students.

Plan to be doing 6–8 hours of work on STA303 each week. In a two-week module, this may be comprised of:

  • 2–4 hours on videos and readings

  • 1–3 hours of attending synchronous class or reviewing the recording and activities

  • 1–2 hours on knowledge basket assessments

  • 2–6 hours on other assessments

  • Remaining time attending reading announcements, office hours, checking Piazza, revision, etc.

3.4.1 Communication

  • Our course discussion board on Piazza is to be used for all content and administration questions. Only sensitive or personal issues/questions should be sent to sta303@utoronto.ca. We reserve the right not to respond to emails that should be Piazza posts.

    • Please ensure all course-related emails include your UTORID. 

  • There are several important forms that you may need if you miss an assessment due to illness or emergency or wish to request a regrade of an assessment.

  • I will use Quercus announcements to share course information and updates. Please make sure you read these. I may also occasionally email or Quercus message you about things that relate specifically to you.

3.5 To do now