6.041 / 6.431 Probabilistic Systems Analysis and Applied Probability

Spring 2005

Dice.

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

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.
Donate Now

Staff

Instructor:
Prof. Muriel Médard

Contributors:
Prof. Dimitri Bertsekas
Prof. John Tsitsiklis

Course Meeting Times

Lectures:
Two sessions / week
1 hour / session

Recitations:
Two sessions / week
1 hour / session

Tutorials:
One session / week
1 hour / session

Level

Undergraduate / Graduate

Archived Courses

Previous version