Math 285 (Stochastic Processes)


Lecture Notes
UCSD Catalog

Math 285 (Driver, Spring 2016) Stochastic Processes


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bulletLast version of the lecture notes has been posted, 6/3/2016.  Have a good summer.
bulletHomework #9 is now posted and lecture notes updated -- 5/26/2016.
bulletHomework #8 is now posted and lecture notes updated -- 5/20/2016.
bulletHomework #7 is now posted and lecture notes updated -- 5/11/2016.
bulletHomework #5 and #6 are now posted and lecture notes updated -- 4/27/2016.
bulletHomework #4 is now posted and lecture notes updated -- 4/20/2016.
bulletHomework #3 is now posted -- 4/13/2016.
bulletThere is one Holiday this quarter; Memorial Day, Monday, May 30.
bulletHomework Assignments are due in class on Fridays starting on April 8. [See homework page.]

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Instructor: Bruce Driver (, AP&M 5260, 534-2648.

Bruce Driver's Office Hours: Monday and Wednesday, 10a-11a in AP&M 5260.

TA (Grader): Tingyi Zhu (,  AP&M  6422.

Meeting times: Lectures are on MWF 9:00a - 9:50a in AP&M B412

Textbook:  Introduction to Stochastic Processes (second edition) by G. Lawler.                    

Auxiliary Text: Essentials of Stochastic Processes (second edition), by Rick Durrett may also be useful. UCSD students may see this book at

Lecture Notes: Supplementary lecture notes will also be posted on this web-site.

Useful Matlab Scripts:

Prerequisites:  The official prerequisite for this course is Math 180A (or an upper-division Introduction to Probability course).

Grading: Your course grade will be based on the homework assignments which are due in class on Fridays. Course grades will be posted on TED (

Course Description:  This course is an introduction to Stochastic Processes for beginning mathematics graduate students and graduate students from other science and engineering disciplines. For mathematics graduate students the course will provide background and motivation for the more advanced year-long sequence Math 280ABC (measure-theoretic probability). Students from other disciplines will find that the course provides a theoretical basis for applied work in stochastic modeling. Topics to be covered include:

bullet Conditional expectations, filtrations, and stopping times.
bullet Markov chains in discrete and continuous time.
bullet Martingales.
bullet Brownian motion.


Jump to Bruce Driver's Homepage.                       Go to list of mathematics course pages.

Last modified on Monday, 14 March 2016 09:53 AM.