Introduction to Mathematical Statistics

Lecture, three hours; discussion, one hour. Requisite: course 100A or Mathematics 170A or 170E. Survey sampling, estimation, testing, data summary, one- and two-sample problems. P/NP or letter grading.

Review Summary

Clarity
0.0 / 10
Organization
1.7 / 10
Time
10-15 hrs/week
Overall
0.0 / 10

Reviews

    Quarter Taken: Fall 2022 In-Person
    Grade: B

    Professor Li is a very kind and caring professor, and he definitely seems genuinely interested with his students learning and discovering meaningful applications of the material taught in 100B. The only issue with Professor Li is his presentation style. He puts up 70 slide slideshows then talks through explaining them with minimal notes by hand. It is very hard to pick up on his thought process, and sometimes how to do the actual math needed when Professor Li is presenting. Allen was an amazing TA however and was always super helpful with HW and even explaining what was wrong on a test.

    Quarter Taken: Fall 2022 In-Person
    Grade: A

    Lectures were pretty disorganized, at least in the way they were presented, although the slides themselves actually contained pretty good material. This class consisted of three in-class exams with no final, which were all open-notes, which I appreciated. Basically, just read the slides and condense it down to the most important concepts/formulas, and use that as a reference during your exams. Tests were mainly computational + R code as far as I recall and generally reasonable. In comparison, the homework is very difficult and hopefully your TA will explain the answers every week in section. There's a lot of material but some of it was certainly interesting in my opinion.

    Quarter Taken: Winter 2023 In-Person
    Grade: N/A

    prof is super nice, but we rarely do practice problems to work thru cohesive examples on how to solve the problems. midterms are super similar to the homework and lecture reviews

    Quarter Taken: Winter 2024 In-Person
    Grade: A

    Disorganized lectures. HW's take ~5 hours every week. HW's must all be typed either in Latex or R. If you have a good TA, it helps. A lot of this class is studying by yourself.

    Quarter Taken: Spring 2024 In-Person
    Grade: B

    This guy is pretty terrible at presenting concepts to you in an efficient and clear way. He makes slide presentations that are literally 80 slides long (although they do have useful information) and rarely goes over examples in class (which I think is really helpful). By the end of the term, I opted to skip all his lectures because I found him to be a really unenthusiastic lecturer who didn't seem to care very much about the students or the class. However, the content itself isn't very difficult, and his tests are pretty fair. They're mostly straightforward exercises that don't ask much about very much conceptual knowledge (plug and chug). I found homework to be a little difficult at first, but the TA was a godsend, who posted discussion videos on Youtube of him literally doing every single problem for you. Participation isn't required but he did take attendance and at the end of the term, he gave those who went to lecture more often extra credit (syllabus said up to 5%). Overall, a doable class that is a tragic reminder of how understaffed the statistics department is.

Course

Instructor
Li, K.
Previously taught
24S 24W 23F 23W 22F

Grading Information

  • No group projects

  • Attendance not required

  • 2 midterms

  • Finals week final

  • 80% recommend the textbook

Previous Grades

Grade distributions not available.