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Concept · from MIT 6.041SC Probabilistic Systems Analysis and Applied Probability

Conditioning and Bayes' Rule

About these materials

MIT's own material for this topic, in MIT's order: Lecture 2: Conditioning and Bayes' Rule.

Source: MIT OpenCourseWare 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013, Prof. John Tsitsiklis — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Order: the items appear in the order MIT's own session page lists them. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.

MIT's session, in MIT's order

MIT 6.041SC · Unit I: Probability Models And Discrete Random Variables · This session on MIT OpenCourseWare ↗

Lecture Topics

  1. Lecture 2: Conditioning and Bayes' Rule VideoLecture video · transcript Watch

Lecture Topics · Recitation Help Videos

  1. A Coin Tossing PuzzleProblem-solving video Watch
  2. Conditional Probability ExampleProblem-solving video Watch
  3. The Monty Hall ProblemProblem-solving video Watch

Where this sits in MIT 6.041SC

Open this session in the full course 6.041SC Probabilistic Systems Analysis and Applied Probability: all units →

MIT OpenCourseWare, Prof. John Tsitsiklis, 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013.

License: CC BY-NC-SA 4.0 · Edition: Fall 2013 · Open the original course on OCW ↗

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