Discrete Stochastic Processes

Diagram of two stable M/M/1 queues.

Tandem queues: A stable M/M/1 queue has a Poisson output at the input rate. The next queue also has a Poisson output at that rate. (Image by MIT OpenCourseWare, adapted from Prof. Robert Gallager's course notes.)


MIT Course Number


As Taught In

Spring 2011



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Course Features

Course Highlights

This course features a complete set of course notes, which provide a more cohesive and complete treatment than is possible in the lecture slides.

Course Description

Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes. The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance.

Robert Gallager. 6.262 Discrete Stochastic Processes, Spring 2011. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu (Accessed). License: Creative Commons BY-NC-SA

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