Part II: Inference & Limit Theorems

The videos in Part II describe the laws of large numbers and introduce the main tools of Bayesian inference methods.

The textbook for this subject is Buy at Amazon Bertsekas, Dimitri, and John Tsitsiklis. Introduction to Probability. 2nd ed. Athena Scientific, 2008. ISBN: 9781886529236.

The authors have made this Selected Summary Material (PDF) available for OCW users.

L = Lecture Content

S = Supplemental Content

SES # & TOPICS SLIDES
Lecture 14: Introduction to Bayesian Inference

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Lecture 14 Slides (PDF - 2.2MB)

Lecture 14 Slides Annotated (PDF - 1.3MB)
Lecture 15: Linear Models With Normal Noise

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Lecture 15 Slides (PDF - 1.8MB)

Lecture 15 Slides Annotated (PDF - 1.8MB)
Lecture 16: Least Mean Squares (LMS) Estimation

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Lecture 16 Slides (PDF - 1.0MB)

Lecture 16 Slides Annotated (PDF - 1.2MB)
Lecture 17: Linear Least Mean Squares (LLMS) Estimation

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Lecture 17 Slides (PDF - 1.0MB)

Lecture 17 Slides Annotated (PDF - 1.2MB)
Lecture 18: Inequalities, Convergence, and the Weak Law of Large Numbers

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Lecture 18 Slides (PDF - 1.3MB)

Lecture 18 Slides Annotated (PDF - 1.9MB)
Lecture 19: The Central Limit Theorem (CLT)

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Lecture 19 Slides (PDF - 2.1MB)

Lecture 19 Slides Annotated (PDF - 2.0MB)
Lecture 20: An Introduction to Classical Statistics

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Lecture 20 Slides (PDF - 1.3MB)

Lecture 20 Slides Annotated