Math 495 - Stochastic Processes - Spring 2003


Topics covered:

Random walks, Markov chains, jump processes, second order processes, and some stochastic differential equations. Prerequisites: Math 493, or permission of instructor.

Course Hours and Room:

MWF 12:00-1:00pm -- Lopata Rm 229

Instructor:

Prof. Albert Baernstein -- Cupples I, Room 201
Phone: (314) 935-6748
Email: al@math.wustl.edu

Unfortunately, Prof. Baernstein's doctors have placed him on a 45 day Injured Reserved List.
In the meantime the course will be taught by:

Prof. Stanley Sawyer -- Cupples I, Room 107
Phone: (314) 935-6703
Email: sawyer@math.wustl.edu

Office Hours:   Sawyer:  

MWF 2:30-3:30pm -- Rm 107 Cupples I    (Note new office hours.)

Links:

Homework Assignments
Albert Baernstein's home page:
Stanley Sawyer's home page
Math 408 home page
Mathematics Department Home Page
Washington University Home Page

Textbook:

Introduction to Stochastic Processes
Hoel, Port, and Stone.   Houghton-Mifflin 1972 or Waveland Press 1987.

Homework:
Some of the exercises in the textbook will be recommended. These are not to be handed in, but to learn the course material you need to do them diligently. There will also be problem sets for you to hand in that will be graded.

About the course:
An introduction to some of the most basic stochastic processes, such as Markov chains and Markov pure jump processes. Students are expected to learn how to do the computations and to achieve a qualitative understanding of the concepts. You'll need a good understanding of undergraduate probability theory at the level of Math 493, but do not need to know any measure theory.

Examinations and course grades:
There will be no exams. In lieu of a final exam, each student will give a lecture or lectures at or near the end of the class on some topic related to the course. Details and suggested topics will be supplied later. Course grade will be mainly determined by performance on the hand-in problem sets and the end-of-course lectures.

Additional reading:
The following books are on one-day reserve in the Math Library:
(The best references are (3) and (4).)
More elementary:
(1) E. Parzen, ``Modern probability theory and its applications'', Chapter 3.6 (12 pages) (Quick once-over)
(2) J. Kemeny and L. Snell, ``Finite Markov Chains''
More detailed:
(3) S. Karlin, ``A first course in stochastic processes'', Chapter 2. (This has many examples of Markov chains in genetics. Detailed and well-written.)
(4) W. Feller, ``An introduction to probability theory and its applications'', Volume I. Chapter XIV (for gambler's ruin) and Chapter XV (Markov chains). (Also detailed and well-written.)
Specifically for branching processes:
(5) T. E. Harris, ``The theory of branching processes'', Springer-Verlag, 1963.

Click here for Albert Baernstein's home page:
Click here for Stanley Sawyer's home page:

Last modified February 26, 2003