6.041 / 6.431 Probabilistic Systems Analysis and Applied Probability, Spring 2005
Name
6-041-spring-2005/contents/index.htm
Size
17.48 KB
Format
HTML
Checksum (MD5)
8888d9ec7b850328713e7721ecbf1984
Author(s)
Bertsekas, Dimitri
Tsitsiklis, John
Médard, Muriel
Alternative Title
Probabilistic Systems Analysis and Applied Probability
Date Issued
June 2005
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.
Subjects
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
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Persistent DSpace Link
