STAT 522: Advanced Theory of Probability
Winter Quarter 2013: Syllabus (last updated 7/17/2012)
Course personnel:
- Professor: Jon A. Wellner
- B320 Padelford Hall
- Phone: 543-6207
- Office hours: 1:30 - 3:30 MWF; or by appointment
Administrative Information:
- Time(s): MWF 11:30 - 12:20
- Place: CMU 228
- I will be absent on January 30, and February 1.
Makeup lectures are scheduled for Friday, January 18 and Friday, February 8
  from 12:30 - 1:20 (in Denny 315)
Prerequisites:
- Mathematical Analysis at the level of Math 424-5-6.
- An interest in probability theory.
- Math/Stat 521
Required Texts:
-
Probability for Statisticians,
by Galen Shorack, 2000. Required.
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.
-
Durrett, R. (1991). Probability: Theory and Examples.
-
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.
Reviews of Recent Books on Statistics and Probability:
Grading:
- Homework: 35%
- Midterm: 30%; Friday, February 15 (during the usual class time)
- Final: 35%
(Scheduled time & date:
2:30 - 4:20, Wednesday, March 20, 2:30 - 4:20
Lectures:
The lectures in 522 will cover parts of Shorack's Chapters
8,and 11-15.
- Chapter 8. Sections 8.4 - 8.6.
- Chapter 11. Convergence in distribution
- Chapter 13. Characteristic functions
- Chapter 14. CLT's via characteristic functions
- Chapter 15. Infinitely divisible and stable distributions
- Chapter 12. Brownian motion and empirical processes.
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