6.041 / 6.431 Probabilistic Systems Analysis and Applied Probability, Spring 2005

Bertsekas, Dimitri; Tsitsiklis, John; Médard, Muriel

Author(s)

Bertsekas, Dimitri; Tsitsiklis, John; Médard, Muriel

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Alternative title

Probabilistic Systems Analysis and Applied Probability

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Abstract

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.

Date issued

2005-06

URI

http://hdl.handle.net/1721.1/70858

Department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Other identifiers

6.041-Spring2005

local: 6.041

local: 6.431

local: IMSCP-MD5-844c8b4a58247e68aef30137b0b67e14

Keywords

probabilistic systems, probabilistic systems analysis, applied probability, uncertainty, uncertainty modeling, uncertainty quantification, analysis of uncertainty, uncertainty analysis, sample space, random variables, transform techniques, simple random processes, probability distribution, Markov process, limit theorem, statistical inference, 6.041, 6.431

Collections

MIT OCW Archived Courses