6.041 / 6.431 Probabilistic Systems Analysis and Applied Probability, Fall 2002

Abstract

Modeling, quantification, and analysis of uncertainty. 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. Interpretations, applications, and lecture demonstrations. Meets with graduate subject 6.431, but assignments differ. From the course home page: 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. The materials are largely based on the textbook, Dynamic Programming and Optimal Control, written by Professors John Tsitsiklis and Dimitri Bertsekas (see http://www.athenasc.com/probbook.html for more information).