Lecture 10: Continuous Random Variables Part III (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)
• L10.6 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)
• L10.10 Detection of a Binary Signal (M-I-T)
• L10.11 Inference of the Bias of a Coin (M-I-T)