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Course Info

  • Course Number / Code:
  • 6.431 (Spring 2005) 
  • Course Title:
  • Probabilistic Systems Analysis and Applied Probability 
  • Course Level:
  • Undergraduate / Graduate 
  • Offered by :
  • Massachusetts Institute of Technology (MIT)
    Massachusetts, United States  
  • Department:
  • Electrical Engineering and Computer Science 
  • Course Instructor(s):
  • Prof. Muriel Médard

    Contributors:
    Prof. Dimitri Bertsekas
    Prof. John Tsitsiklis 
  • Course Introduction:
  •  


  • 6.041 / 6.431 Probabilistic Systems Analysis and Applied Probability



    Spring 2005




    Course Highlights


    This course features a full set of lecture notes and detailed problem sets in the assignments section, in addition to quizzes and other materials used by students in the course. The materials are largely based on the textbook, Introduction to Probability, written by Professors John Tsitsiklis and Dimitri Bertsekas.


    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.
     

ACKNOWLEDGEMENT:
This course content is a redistribution of MIT Open Courses. Access to the course materials is free to all users.






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