Unlike the class description in the catalog, this class is highly theoretical. Most of the lectures are of her deriving the various different models and techniques used in statistical linear modeling. In addition, she did a flipped classroom method where we watched recorded videos and then came to lecture, but the in-person lecture was basically the same as the recorded video.

Homeworks are long and tedious, with what felt like repetitive coding problems and challenging theory questions. There's a final paper/presentation worth 50% of the grade, but the rubric is not very clear. But the grading wasn't too harsh, so it balanced out.

Due to the contradiction between the class description and what's actually taught in class, I'd suggest only taking it if you want a more theoretical learning to these concepts.

STATS 100B with Prof Li (Jessica) is tough, but only because the course itself is tough. Jessica teaches very well in class and always stops midway to ask if anybody has questions. She also willingly and patiently answers every question she is posed to clarify some of the things that she teaches. Her tests are deceptively easy, but actually quite challenging indeed. She doesn't have finals, she has 3 midterms instead, with the 3rd midterm having double weightage. One good thing is that she sets 1 bonus question per exam that allow you to regain some points that you might have carelessly lost otherwise, which is great! The bonus questions are challenging, but they do not cover material that she did not go through in class, so they are doable to a degree, as long as you complete the rest of the tests quickly enough. She gives 1 homework every week all of which are very manageable and she does not give homeworks during weeks when we have midterms. Also, she's very willing to help out with questions posed on CCLE or during her office hours.