STAT 521: Advanced Theory of Probability
Fall Quarter 2019: Syllabus (last updated 08/14/2019)
Course personnel:
- Professor: Jon A. Wellner
- B320 Padelford Hall
- Phone: 543-6207
- Office hours:
1:30 - 3:30 MF;
8:30 - 10:00 Tuesday (CSSS conference room);
or by appointment.
Administrative Information:
- Time(s): MWF 11:30 - 12:20
- Place: Low 106
- I will be absent on Wednesday, September 25.
Make up for the missed lecture on 25 September.
Friday 25 October from 8:30 - 9:20 AM, Low 101
Prerequisites:
- Mathematical Analysis at the level of Math 424-5-6.
- An interest in probability theory.
Required Texts:
-
Probability: Theory and Examples, 5th edition,
by Rick Durrett, 2019. Required.
-
Probability for Statisticians, by Galen Shorack.
Online version from 2012.
Recommended.
Supplemental probability texts:
-
Billingsley, P., (1986). Probability and Measure.
-
Breiman, L., (1968). Probability.
-
Chow, Y.S., and Teicher, H. (1978). Probability Theory.
-
Chung, K. L., (1974). A Course in Probability Theory.
-
Dudley, R. M. (2002). Real Analysis and Probability.
-
Feller, W. (1957). An Introduction to Probability Theory and
Its Applications, Volume I.
-
Feller, W. (1966). An Introduction to Probability Theory and
Its Applications, Volume II.
-
Kallenberg, O. (1997). Foundations of Modern Probability
-
Lo\'eve, M., Probability Theory, I and II.
-
Williams, D, Probability with Martingales.
Supplemental analysis and measure theory texts:
-
Bartle, R. G. (1966). The Elements of Integration.
-
Cohn, D. (1980). Measure Theory.
-
Royden, H. L. (1963). Real Analysis.
-
Rudin, W. (1964). Principles of Mathematical Analysis.
Grading:
- Homework: 35%
- Midterm: 30% (November 1, 2019)
- Final: 35%
(Scheduled time & date: Wednesday, December 11, 2019, 2:30 - 4:20 PM)
Lectures:
The lectures in 521 will cover parts of Shorack's Chapters
1 - 5, 8 - 10.
- Chapter 1. Measures
- Chapter 2. Measurable Functions and Convergence
- Chapter 3. Integration
- Chapter 4. Derivatives via signed measures
- Chapter 5. Measures and Processes on Products
- Chapter 8. Independence and Conditional Distributions
- Chapter 9. Special Distributions
- Chapter 10. WLLN, SLLN, LIL, and Series
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