STAT 6120

This class is really quite poor and I have to put most of the blame on Shan Yu. While Shan is very nice and approachable, pedagogically speaking she is quite poor. Her lectures were highly theoretical and I can say with certainty that only a few people in our class followed along with what she was saying. In terms of assignments the homeworks were also very difficult and if you are not fluent in linear algebra you are going to struggle. The midterm was actually quite different than what we were doing in lectures and homeworks, since it was more applied stuff. She did give us a practice midterm, but it was significantly easier than the actual midterm. Linear models is a required course for MS students for a good reason, but the instruction was so poor I really don't feel like I came away with very much. After having Prof. Yu for both 5630 and 6120 I can say that her teaching style does not fit the needs of the majority of students. I’m sorry to say, but this class is just poor across the board. 

Towards the end of the semester it seemed like Prof. Yu kind of checked out. She stopped responding to some people’s emails and generally seemed to struggle in the lectures. After our final exam she never entered our exam score into collab. I would like to think that she did this just to save time, but I’m honestly not sure she even graded it. 

Perhaps if you have a stronger math background then you would have a better understanding in this class, but the people that I knew basically had to learn most of the content on their own. I wish classes like these wouldn’t exist, but sadly they do. A complete redesign of this class is necessary to be even remotely useful to the majority of students and it starts with getting rid of Prof. Yu.

#tCFfall22

Love Shan Yu! She's a relatively new professor to UVA, but after having had her for STAT 5630 (machine learning) and STAT 6120 (this course) she is easily one of my favorite stats professors I've had while at UVA.

Breakdown of course: 30% HW (7 total assignments); 30% Midterm; 40% final project

Lecture: Lectures were mainly theoretical, with some R applications towards the end of the lecture most of the times. I would recommend showing up to lecture whenever you can, because though her slides are helpful, she heavily supplements them during lecture. Though she posts the annotated slides afterwards, they're often difficult to understand if you weren't there during lecture.

HW: There are 7 HW assignments during the course. Similar to her 5630 course, for whatever reason the 1st HW seems to be graded much more harshly than the rest of the class (I got a 50% on the first in 5630 and 70% on the first in this class and ended up getting an A in both). HWs vary in difficulty: some take only 2 hours while others can take a bit longer. Overall, if you pay attention during lecture it isn't hard to average around a 95% on them. Also, she's very helpful during office hours if you have any questions and sometimes emails us hints for certain questions if enough people have issues with them.

Midterm: She sends out a practice midterm about a week before the exam and you should definitely do it. The real midterm was extremely similar in both form and content to the practice. She also allows a sheet from and back for formulas/ proofs which was helpful. Overall, the midterm was pretty easy in my opinion, especially if you filled out your formula sheet and looked over the practice exam beforehand.

Project: A bit different than standard statistics final projects, Professor Yu sends out the project on Friday and you have until Monday to finish it. She basically gives you a series of questions regarding a data set and wants you to answer them using R. It's basically just a really long HW. I did it the day before it was due (sorta dumb-- took me basically all day) but I ended up getting a 95% on it and didn't end up making it to the last few lectures so it's graded nicely.

Overall, this is a required course so there's no way around taking it if you're an MS of phd student. However, Professor Yu is a great professor so if you have the chance to take it with her you should and it won't be a hassle by any means.

#tCFfall2021