Please read the syllabus. It has important information about the course, including structure, assignments, grading, and office hours, among many others. Even Snoop Dog wants you to read the syllabus!

Welcome to STA 235H!

Our class meets on one of these four schedules (depending on your section):

  • Section 1 - 05430: Mon 10:00 AM – 12:00 PM, SZB - 3.508
  • Section 2 - 05435: Mon 12:00 PM – 2:00 PM, SZB - 2.802
  • Section 3 - 05440: Wed 2:00 PM – 4:00 PM, UTC 3.122
  • Section 4 - 05445: Mon 4:00 PM – 6:00 PM, UTC 4.110

The objective of this course is for you to gain the tools you need to tackle real-world problems from a quantitative perspective. We will be covering topics on regression modelling, causal inference, and predictive modelling. You will have the opportunity to be exposed to an array of different real-world examples, get hands-on experience in working with data, and improve your R coding skills for data science.

Your success in this class is important to me, and my goal is for you to learn everything you were hoping to learn in this class. I have accommodations in place to allow you to complete the requirements of this course, but if you feel you need additional accommodations, please reach out.

If you feel you are falling behind or that there are any aspects of this class that are preventing you from learning, reach out to me or a teaching assistant as soon as possible, so we can work something out. We also encourage you to reach out to the student resources available through UT, many of which are listed on this syllabus.


The Syllabus has important information, so please check out the different sections. To help you to retain the most important points of this document, here’s the summarized version of the main highlights:

  • Be nice 😄
  • Focus on understanding concepts and not on memorizing 💡
  • Ask questions! (in class and during office hours) 🙋‍♀️
  • If you fall behind, reach out 😖

There are different assignments to be completed in this class, including homework assignments, Just In Time Teaching assignments, a midterm, and a final exam. Additionally, part of your grade will depend on attendance and participation.

You will be able to drop some assignments to accommodate students that have unforeseeable issues, so check out the specifics in the Grading section.

Finally, make sure you check the Canvas announcements periodically (turn on your notifications!).

© Magdalena Bennett - licensed under Creative Commons.