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
10.0 / 10
Organization
6.7 / 10
Time
0-5 hrs/week
Overall
10.0 / 10

Reviews

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

    great class, nice prof. His lectures are very engaging

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

    Good professor, enjoyed the Kaggle competition

Course

Instructor
Akram M. Almohalwas
Previously taught
24F 23F 22F 21F 21Su 20F 20Su 18F 18Su 18S 17S

Grading Information

  • Has a group project

  • Attendance required

  • 1 midterm

  • Finals week final

  • 50% recommend the textbook