Introduction to Data Analysis and Regression

Lecture, three hours; discussion, one hour. Requisites: one course from course 10, 12, 13, 15, Economics 41, or Psychology 100A, or score of 4 or higher on Advanced Placement Statistics Examination, and course 20. Recommended: course 102A. 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
10.0 / 10
Time
10-15 hrs/week
Overall
10.0 / 10

Reviews

    Quarter Taken: Winter 2023 In-Person
    Grade: A

    Great class, the professor is nice, there was a final project at the end of the class but it was doable, the professor was very supportive.

    Quarter Taken: Winter 2023 In-Person
    Grade: A

    So incredibly boring but also very easy. Ngl I did not retain any information from this class. If you are actually interested in linear regression, I would suggest taking Stats 100C at the same time as this class since 100C is more theoretical whereas this class is purely application. Linda is sweet but very dry and lectures are basically naptime if you choose to attend. A good class to take when you're taking 4 classes because its so easy

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

    Overall, an easy class. The professor assigned homework almost weekly that was very simple but time consuming. We had both an online midterm and final that consisted of questions much more difficult than the homework. We also had a final project where we picked a dataset and fit the best linear model to the data.

Course

Instructor
Linda Zanontian
Previously taught
23W

Grading Information

  • No group projects

  • Attendance not required

  • 1 midterm

  • 10th week final

  • 33% recommend the textbook

Previous Grades

Grade distributions not available.