Probabilistic Systems Analysis and Applied Probability

This course features a full set of lecture notes and problem sets introducing 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.
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Author Name: 
Muriel Medard, John Tsitsiklis, Dimitri Bertsekas
Technical Requirements: 
Adobe Acrobat Reader
Source Code Available: 
Source Code Available
Intended User Role: 
Learner, Teacher
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Copyrights: 
Yes
Cost: 
Free for All
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