Statistics 210a: Theoretical Statistics
UC Berkeley, Fall 2026
Stat 210A is an introductory Ph.D.-level course in theoretical statistics. It is a fast-paced and demanding course intended to prepare students for research careers in statistics.
Course enrollment for undergraduates
If you are an undergraduate who wants to take this course, please fill out the permission code request form to let me know about your background. If you are unsure of your background, you can check the frequently asked questions regarding preparation and review materials.
Resources
- Syllabus for basic course information
- Gradescope for turning in homework
- EdStem for announcements and technical discussion (no homework spoilers!)
- bCourses for lecture videos and homework solutions
Schedule
Week 1
| Aug 27: | Lecture 1 Introduction | Handwritten notes |
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Week 2
| Sep 1: | Lecture 2 Probability | Handwritten notes |
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| Sep 3: | Lecture 3 Estimation | Handwritten notes |
Week 3
| Sep 8: | Lecture 4 Sufficiency | Handwritten notes |
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| Sep 9: | Homework 1 Problems | LaTeX source |
| Sep 10: | Lecture 5 Exponential Families | Handwritten notes |
Week 4
| Sep 15: | Lecture 6 Exponential Families (2nd lecture) | Handwritten notes |
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| Sep 16: | Homework 2 Problems | LaTeX source |
| Sep 17: | Lecture 7 Completeness | Handwritten notes |
Week 5
| Sep 22: | Lecture 8 Unbiased Estimation | Handwritten notes |
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| Sep 23: | Homework 3 Problems | LaTeX source |
| Sep 24: | Lecture 9 Score and Fisher Information | Handwritten notes |
Week 6
| Sep 29: | Lecture 10 Bayes Estimation | Handwritten notes |
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| Sep 30: | Homework 4 Problems | LaTeX source |
| Oct 1: | Lecture 11 Interpretation and Choice of Prior | Handwritten notes |
Week 7
| Oct 6: | Lecture 12 Bayesian Computation | Handwritten notes |
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| Oct 7: | Homework 5 Problems | LaTeX source |
| Oct 8: | Lecture 13 James--Stein Estimator | Handwritten notes |
Week 8
| Oct 13: | Lecture 14 Minimax Estimation | Handwritten notes |
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| Oct 14: | Homework 6 Problems | Data LaTeX source |
| Oct 15: | Lecture 15 TBD (extra lecture) |
Week 9
| Oct 20: | Lecture 16 Hypothesis Testing | Handwritten notes |
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| Oct 21: | Homework 7 Problems | LaTeX source |
| Oct 22: | Lecture 17 Testing with one parameter | Handwritten notes |
Week 10
| Oct 27: | Lecture 18 p-values and confidence intervals | Handwritten notes |
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| Oct 28: | Homework 8 Problems | LaTeX source |
| Oct 29: | Lecture 19 Testing with nuisance parameters | Handwritten notes |
Week 11
| Nov 3: | Lecture 20 Testing in linear models | Handwritten notes |
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| Nov 4: | Homework 9 Problems | LaTeX source |
| Nov 5: | Lecture 21 Testing in linear models (second lecture) | Handwritten notes |
Week 12
| Nov 10: | Lecture 22 Asymptotics | Handwritten notes |
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| Nov 12: | Lecture 23 Maximum likelihood estimation | Handwritten notes |
| Homework 10 Problems | LaTeX source Data for problem 3 |
Week 13
| Nov 17: | Lecture 24 MLE Consistency | Handwritten notes |
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| Nov 18: | Homework 11 Problems | LaTeX source |
| Nov 19: | Lecture 25 Likelihood-based Inference | Handwritten notes |
Week 14
| Nov 24: | Lecture 26 Bootstrap (on Zoom) | Handwritten notes |
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Week 15
| Dec 1: | Lecture 27 Multiple Testing (Part I) | Handwritten notes |
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| Dec 2: | Homework 12 Problems | LaTeX source |
| Dec 3: | Lecture 28 Multiple Testing (Part II) | Handwritten notes |
Week 17
| Dec 15: | Exam Final Exam, 8-11am |
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