| 1 |  Conditional Probability, Bayes' Rule and Independence (PDF)
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| 2 | Discrete Probability Models (PDF) | |
| 3 | Continuous Probability Models I & II (PDF - 2.1MB) | Figures for lecture 3: Probability Models Applied to Data (PDF) |
| 4 | Joint Distributions and Independent Random Variables (PDF - 1.7MB) |
Figures for Lecture 4: Multivariate Gaussian Distribution, Part 1 (PDF) Figures for Lecture 4: Multivariate Gaussian Distribution, Part 2 (PDF)
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| 5 | Conditional Distributions and Functions of Jointly Distributed Random Variables I & II (PDF - 1.7MB) | |
| 6 | Moment Generating Functions I & II (PDF - 2.1MB) | |
| 7 | The Law of Large Numbers and the Central Limit Theorem (PDF) | Lecture 7 Addendum: The Law of Large Numbers and the Central Limit Theorem, (PDF) |
| 8 | Method-of-Moments Estimation (PDF - 1.7MB) | |
| 9 | Likelihood Theory I & II (PDF - 1.5MB) | Lecture 9 Addendum: The Observed Fisher Information and Fisher Information for the Binomial Model (PDF) |
| 10.1 | Bayesian Methods (PDF) | |
| 10.2 | Corrigienda (PDF) | Figures for lecture 10: Bayesian Analyses, Beta Probability Models (PDF) |
| 11 | Bootstrap and Monte Carlo Methods (PDF - 1.4MB) | |
| 12 | Hypothesis Testing I & II (PDF - 2.3MB) | |
| 13 | Simple Regression Model I, II & III (PDF - 1.4MB) | Lecture 13 Addendum: The Meaning of Regression (PDF) |
| 14 | Analysis of Variance (PDF - 1.2MB) | |
