This is an archived course. A more recent version may be available at

Archived Versions

Probabilistic Systems Analysis and Applied Probability

As taught in: Spring 2005

A photograph of two dice.

Two Dice. (Image courtesy of National Parks Service Museums.)


Prof. Dimitri Bertsekas

Prof. John Tsitsiklis

Prof. Muriel Médard

MIT Course Number:

6.041 / 6.431


Undergraduate / Graduate

Course Features

Course Highlights

This course features a full set of lecture notes and detailed problem sets in the assignments section, in addition to quizzes and other materials used by students in the course. The materials are largely based on the textbook, Introduction to Probability, written by Professors John Tsitsiklis and Dimitri Bertsekas.

Course Description

This course is offered both to undergraduates (6.041) and graduates (6.431), but the assignments differ. 6.041/6.431 introduces students to the modeling, quantification, and analysis of uncertainty. Topics covered include: formulation and solution in sample space, random variables, transform techniques, simple random processes and their probability distributions, Markov processes, limit theorems, and elements of statistical inference.