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Probabilistic Systems Analysis and Applied Probability

OCW Scholar

Images of chess, poker, dice, weather map, data stream, and a Markov chain.

Examples of the tools and applications of probability theory.

Instructor(s)

Level

Undergraduate

Cite This Course

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Course Features

Course Description

This course introduces students to the modeling, quantification, and analysis of uncertainty.  The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management.

Course Format


Click to get started. This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:

  • Lecture Videos by MIT Professor John Tsitsiklis
  • Lecture Slides and Readings
  • Recitation Problems and Solutions
  • Recitation Help Videos by MIT Teaching Assistants
  • Tutorial Problems and Solutions
  • Tutorial Help Videos by MIT Teaching Assistants
  • Problem Sets with Solutions
  • Exams with Solutions

 

MITx Versions

MITx offers a free version of this subject on edX. Please register to get started:

Tsitsiklis, John. 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013. (MIT OpenCourseWare: Massachusetts Institute of Technology), http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041sc-probabilistic-systems-analysis-and-applied-probability-fall-2013 (Accessed). License: Creative Commons BY-NC-SA


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