Statistics 210A: Theoretical Statistics (Fall 2017)
Course Information
Prof. Will Fithian (Instructor)
Xiao Li (GSI)
Lectures TuTh 12:302, Wheeler 222
Final Exam Th Dec 14, 36pm, location TBD
Syllabus
Announcements, homework, handouts at bCourses
Piazza discussion site for technical questions (no homework spoilers!)
Materials
Materials from class:
Aug. 29: demo of exponential tilting
Sep. 21: demo of Bayesian inference for the BetaBinomial distribution
Oct. 3: demo of Bayes, hierarchical Bayes, and JamesStein
Assignments:
Content
Stat 210A is Berkeley's introductory Ph.D.level course on theoretical statistics. It is a fastpaced and demanding course intended to prepare students for research careers in statistics.
Topics:
Statistical decision theory, frequentist and Bayesian
Exponential families
Point estimation
Hypothesis testing
Resampling methods
Estimating equations and maximum likelihood
Empirical Bayes
Largesample theory
Highdimensional testing
Multiple testing and selective inference
Prerequisites:
References
All texts are available online from Springer Link.
Main text:
Supplementary texts:
Grading
Your final grade is based on:
Weekly problem sets: 50%
Final exam: 50%
Lateness policy: Late problem sets will not be accepted, but you will get to drop one grade.
Collaboration policy: For homework, you are welcome to work with each other or consult articles or textbooks online, but
You must write up the problem by yourself.
You may NOT consult any solutions for previous iterations of this course.
If you collaborate or use any resources other than course texts, you must acknowledge your collaborators and the resources you used.
Academic integrity: You are expected to abide by the Berkeley honor code. Violating the collaboration policy, or cheating in any other way, will result in a failing grade for the semester.
Reading Assignments
Date  Reading 
Aug. 24  Chap. 1 and Sec. 3.1 of Keener 
Aug. 29  Chap. 2 of Keener 
Aug. 31  Chap. 2 and Sec. 3.2 of Keener 
Sep. 5  Secs. 3.4, 3.5, and 3.6 of Keener 
Sep. 7  Secs. 3.6 and 4.1 of Keener 
Sep. 12  Secs. 4.1 and 4.2 of Keener 
Sep. 14  Secs. 4.5 and 4.6 of Keener 
Sep. 19  Secs. 7.1 and 7.2 of Keener 
Sep. 21  Secs. 7.1 and 7.2 of Keener 
Sep. 26  Secs. 7.2 and 11.1 of Keener 
Sep. 28  Secs. 7.2 and 11.1 of Keener 
Oct. 3  Secs. 11.1, 11.2 and 9.4 of Keener 
Oct. 5  Secs. 12.1, 12.2, 12.3 and 12.4 of Keener 
Oct. 10  Secs. 12.3, 12.4, 12.5, 12.6 and 12.7 of Keener 
Oct. 12  Secs. 13.1, 13.2, and 13.3 of Keener 
Oct. 17  Secs. 13.1, 13.2, and 13.3 of Keener 
Oct. 19  Secs. 13.1, 13.2, and 13.3 of Keener 
Oct. 24  Secs. 14.1, 14.2, 14.4, 14.5, and 14.7 of Keener 
Oct. 26  Secs. 8.1, 8.2, and 8.3 of Keener 
Oct. 31  Secs. 8.3 and 8.4 of Keener 
Nov. 2  Secs. 8.5, 9.1, and 9.2 of Keener 
Nov. 7  Secs. 9.1, 9.2, and 9.3 of Keener 
Nov. 9  Secs. 9.1, 9.2, and 9.3 of Keener 
Nov. 14  Secs. 9.5 and 9.7 of Keener 
Nov. 16  Secs. 19.1 – 19.3 of Keener; 15.1 – 15.4 of Lehmann & Romano 
Nov. 21  Lecs. 2 and 3 of Candes 
Nov. 23  No class. Happy Thanksgiving! 
Nov. 28  Lec. 6 of Candes 
Nov. 30  Lecs. 8 and 9 of Candes

