PSTAT 213A -- An introduction to probability and random processes -- FALL
2006
Lectures: |
TR 9.30-10.45 |
BUCH 1934 |
Discussion: |
W 9.00-9.50 |
GIRV 1106 |
Raya's Office Hours: |
TR 11-11:50 am |
SH5516 |
The goal of the PSTAT 213ABC series is to give a rigorous introduction to
probability and random processes. The combination of PSTAT 213ABC and PSTAT 210
is designed for those requiring a thorough understanding of basic probability theory
and is thus aimed at students who plan to do research in statistics,
applied probability, mathematical finance, economics, biology, computer science, or engineering.
PSTAT 213A gives an introduction to Markov Chains and related processes without the use of measure theory.
We will be emphasizing major ideas and techniques with long proofs sometimes being
presented in outline.
Prerequisites
Introductory course on probability and statistics (PSTAT120AB or equivalent).
A knowledge of basic measure theory (the theory of Lebesgue integration
in particular) is required for PSTAT 213BC, but not PSTAT 213A.
Students who lack such a background are advised to either enroll in PSTAT
210 (can be taken concurrently with PSTAT 213A) or to complete MATH
118ABC and MATH 201AB (or equivalent). Analysis background is helpful but not
necessary for PSTAT 213A.
Main texts for PSTAT 213A
S. Resnick, Adventures in Stochastic Processes.
G. R. Grimmett and D. R. Stirzaker, Probability and Random Processes,
Third Edition..
Other references
R. Durrett, Probability: Theory and Examples, Second or Third Edition.
S. Karlin and H. Taylor, A First Course in Stochastic Processes.
L. Breiman, Probability.
PSTAT 213A Topics
-
Generating functions; random walks and branching processes (Chapter 1)
-
Discrete time Markov chains (Chapter 2).
-
Continuous time Markov chains; birth-death processes, queues (Chapter 5).
-
The Poisson process and Point Processes (Chapter 4).
Raisa ("Raya") Feldman
Email me at: feldman@pstat.ucsb.edu
Last revision: September 27, 2006