**
**Math 180C (Driver, Spring 2008) Introduction to
Probability

*
(http://math.ucsd.edu/~driver/180C-Spring2008/index.htm)*

**
****Instructor: **Bruce
Driver (driver@math.ucsd.edu),
AP&M 7414, 534-2648.** Office Hours: **Wednesday
and Friday,
1-2 PM or by appointment.

**TA: **Teng Gao
(tgao@math.ucsd.edu), AP&M
5412. **Office Hours: **
Tuesday and Thursday 4 to 5pm.

**Finals Week Office Hours: **

Bruce: M & T: 2 - 3

Mike: M: 1-3 and T: 1-5

**Meeting times: **Lectures are on MWF
09:00a - 09:50a in
YORK 4080A. Sections are on Mondays in HSS 1305 from 5:00p -
5:50p.

**Textbook:** *An Introduction to
Stochastic Modeling* by S. Karlin and H. Taylor, 3rd edition. There may also be some extra notes which will be
distributed on this web-page at "Lecture Notes."

Prerequisites: Math 180A-B.

**Homework:** Homework is due at the
beginning of **Monday's **section (unless otherwise specified).
Alternatively, you can drop it in the TA's box on the 6th floor of Applied
Physics and Mathematics before 5:00 PM on the due date. It will be
selectively graded and returned. You are encouraged to get help with the
homework when needed. You are also encouraged to cooperate with your fellow
classmates. **However, **it is **NOT **permissible to simply copy someone
else's homework solutions -- you must write up your final solutions
independently. No late homework will be accepted.
Please see the Home-work page for all homework
assignments.

**Test times: **Midterm: Friday, May 9 at 9:00AM in class. Final exam:
Wednesday, June 11 at 8:00 -- 11:00 AM in
YORK 4080A.

**Grading: **
*
***Final Grade **=
homework (30%)+ midterm (30%
each) + final (40%)

**Goals of the Course. **We will continue the
introduction to stochastic processes begun in 180B. In terms of the book, we
will be covering much of the material in chapters VI, VII, and VIII and the end
of chapter IV which include the following topics.

- Long time behavior of discrete space and time Markov chains.
- Discrete state space Markov chains in continuous time.
- Renewal Processes.
- Brownian Motion.

Topics 2. and 3. generalize the notion of Poisson process in two different
ways. Brownian motion is one of the two building blocks of the subject of
stochastic processes (along with the Poisson Process). Time permitting, we
may cover some topics from the theory of Branching processes or the theory of
queues (waiting lines).

**Prerequisites**- Math 180A-B or consent of the
instructor.