Introduction to Statistical Models and Data Mining

Lecture, three hours; discussion, one hour. Enforced requisite: course 101A. Recommended: course 101B. Designed for juniors/seniors. Applied regression analysis, with emphasis on general linear model (e.g., multiple regression) and generalized linear model (e.g., logistic regression). Special attention to modern extensions of regression, including regression diagnostics, graphical procedures, and bootstrapping for statistical influence. P/NP or letter grading.

Review Summary

Clarity
8.3 / 10
Organization
10.0 / 10
Time
0-5 hrs/week
Overall
10.0 / 10

Enrollment Progress

Jul 13, 4 PM PDT
LEC 1: 80/80 seats taken (Full)
LEC 2: 80/80 seats taken (Full)
First passPriority passSecond pass2 days5 days8 days11 days14 days17 days20 days23 days26 days020406080100

Section List

  • LEC 1

    Closed

    TR 9:30am-10:45am

    Franz Hall 2258A

    Review

  • LEC 2

    Closed

    TR 12:30pm-1:45pm

    Renee and David Kaplan Hall 135

    Review

Reviews

    Quarter Taken: Fall 2022 In-Person
    Grade: A+

    Shirong is the GOAT. Very generous grading policy that gives you the opportunity to really learn the material. I recommend going to lectures since they are very informative on machine learning models. The group project was pretty fun since I had a great group, and I recommend asking Professor Xu for help – he cares a lot for his students. Highly recommend taking this class, it was a lot of fun!

Course

Instructor
Xu, S.
Previously taught
24F 23F 22F

Grading Information

  • Has a group project

  • Attendance not required

  • 1 midterm

  • No final

  • 0% recommend the textbook

Previous Grades

Grade distributions not available.