STAT210B: Theoretical Statistics

Description

Instructor: Song Mei (songmei [at] berkeley.edu)
Lectures: Tuesday/Thursday 11:00-12:30. Social Sciences Building 20.
Office Hours: Tu 2 - 4 pm. Evans 387.
GSI: Licong Lin (liconglin [at] berkeley.edu)
Office Hours: Fr 9 - 11 am. Evans 444.

This is an advanced graduate course on mathematical statistics, following up on the introductory course STAT 210A. Topics to be covered include tail bounds and basic aspects of concentration of measure, uniform laws of large number, metric entropy and chaining arguments, Gaussian comparison inequalities, covariance estimation and non-asymptotic random matrix theory, sparse high-dimensional models, structured forms of principal component analysis, non-parametric regression, and minimax lower bounds.

Announcements

• First lecture starts on Jan 17, 2023 (Tuesday).

• For undergraduates who would like to enroll, the enrollment code will not be ready until the first week of the class. You can contact the instructor by then.

• Please find course materials on bCourse.

• Please use Gradescope for HW submissions. Entry code: V5ZV67.

• Please use Ed for questions.

Prerequisite

All students should have taken STAT 210A or an equivalent course in basic mathematical statistics, and must have a strong background in probability and real analysis. This course requires some degree of mathematical maturity.

Grading

• Class attendance is required.

• Each student is required to scribe at least 1 lecture. Please use this template for scribe. Please sign up scribing here.

• There will be 5-6 homeworks. Late submissions will get a deduction of 15 % per late day.

• In class mid-term. Date TBA.

• Final exam. Date Location TBA.

• Final grade will be Homework x 30 % + mid-term x 25 % + final x 40 % + scribe x 5 %.

Topics