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Introduction to Probability (Spring 2018) (M-I-T)
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Part I: The Fundamentals (M-I-T)
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Lecture 10: Continuous Random Variables Part III (M-I-T)
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L10.6 Stick-Breaking Example (M-I-T)
L10.6 Stick-Breaking Example (M-I-T)
Course:
Lecture 10: Continuous Random Variables Part III (M-I-T)
Discipline:
Applied Sciences
Institute:
MIT
Instructor(s):
Prof. John Tsitsiklis, Prof. Patrick Jaillet
Level:
Graduate
Lecture 10: Continuous Random Variables Part III (M-I-T)
L10.10 Detection of a Binary Signal (M-I-T)
L10.11 Inference of the Bias of a Coin (M-I-T)
L10.1 Lecture Overview (M-I-T)
L10.2 Conditional PDFs (M-I-T)
L10.3 Comments on Conditional PDFs (M-I-T)
L10.4 Total Probability & Total Expectation Theorems (M-I-T)
L10.5 Independence (M-I-T)
L10.6 Stick-Breaking Example (M-I-T)
L10.7 Independent Normals (M-I-T)
L10.8 Bayes Rule Variations (M-I-T)
L10.9 Mixed Bayes Rule (M-I-T)