CS 616 Stochastic Models in Computer Science

CSCI 616-01, Fall 2007



Where and When

Class:                10.00-10.50, Monday, Wednesday, Friday,                Morton 303
Office hours:      15.00-17.00, Monday, Wednesday and other hours by appointment.

Midterm exam:   October 19, 2007

Final exam:        not determined yet.



Peter Kemper
006 McGlothlin-Street Hall (my room is in between Dr. Kearns office in 005 and that of 007)
kemper [At] CS [dot] WM [dot] EDU


An introduction to probability theory and stochastic models, as they apply to computer science. Key terms are random variables, probability distributions (e.g., uniform, geometric, exponential, Poisson), joint distributions, limit theorems, conditional probability and conditional expectation. We will also consider Markov chains, a particular stochastic process that is frequently applied in stochastic modeling of computer and communication systems.


Basic concepts of calculus, linear algebra, and discrete mathematics. No probability background is required.

Required Book:

Sheldon M. Ross, Introduction to Probability Models, 9th edition, Academic Press.(The 9th edition is the most recent, previous ones may serve as well.)

Lectures will be mainly based on this text. Lecture material will be supplemented by appropriate reference documents. 

Required Work:

Homeworks (usually 8 to 10):                  40% of the grade

Project (requires some programming):     10% of the grade

In-class midterm:                                     20% of the grade

In-class final:                                           30% of the grade


The final numeric grade will be mapped into a letter grade Ňon a curve.Ó Generally, 90 and above is an A; 80 to 89 is a B, etc., however if necessary, a downward adjustment may take place.

Late Work Policy

Assignments come with a submission deadline and a drop out deadline. The submission deadline is when you are supposed to hand in your results. The drop out deadline is a little later. An assignment that you hand in before the drop out deadline will be considered and graded.  An assignment that you hand in after the drop out deadline will NOT be considered and NOT graded.
So it is highly recommended to plan ahead and work with submission deadlines and keep the time buffer between submission and drop out deadlines for unforeseen emergencies.  Deadlines will be set well in advance. If you have a justifiable reason (such as an illness) for not turning in a homework on time or to miss an in-class test, you have to inform me as soon as you can and certainly before the deadline.


It is expected that students attend all classes.

Students Who Need Accommodation:

Please see me after class or send email to set up a brief meeting.

Information Dissemination:

I will maintain a set of web pages beneath


in support of the course. They should be considered official components of the course, and you should check them on a daily basis.