Taught by Michael Wallace, who is Biostatistician. He is passionate about what he is teaching and good slides, fair exam (not midterm 2…). So it would be good to do research with him. His research interest from his website:

My primary research interest is in causal inference, with a specific focus on dynamic treatment regimes (DTRs) and personalized medicine. Dynamic treatment regimes are sequences of decision rules that take subject-level data (such as age, health status, or prior treatment) as input and recommend actions (such as which drug to take) as output. Working with longitudinal datasets, my work focuses on deriving methodologies that help identify the sequence of treatment decisions that yields the best expected outcome.

More generally, I’m interested in identifying new ways to apply methods from different disciplines in new settings. This includes modifying methodology from one area of statistics so that it may be applied in a different area (such as applying measurement error techniques to dynamic treatment regime problems), or through applying statistical methods to novel problems in the ‘real world’ of data analysis.

Once I asked him whether he would hire any URA (undergraduate research assistant). Most likely no, because

which is not just a matter of grades, but whether their interests/ambitions align closely with my research.

Let’s get back to the course content… It’s more like a broad introduction to statistics with unorganized contents… It’s hard to understand what’s going on behind the material because the time doesn’t allow that… So only thing you could do it’s to know the formula… If you are really into these material, consider learning more in your masters.

It teaches you R in R assignments… which is dumb. Just need to copy the code and run them. Maybe a few definition questions.

So be prepared and go to lectures.

Also you should definitely take stat 241 if possible. Everything should be clear in that course. Wallace is teaching it during winter 2019, but I couldn’t attend :(