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.