Spring 2022 - Ani Adhikari
Spring 2022 - Ani Adhikari
| Week | Content | Assignments |
|---|---|---|
| 1 | Probability — axioms, rules, approximation Random variables - distributions, equality, conditioning |
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| 2 | Symmetry and collections of events Binomial and related counts; a Poisson limit |
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| 3 | Independence and Poissonization Expectation |
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| 4 | Expectation and Additivity Expectation by Conditioning |
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| 5 | Long run behavior of Markov Chains Balance |
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| 6 | Markov Chain Monte Carlo SD and tail bounds |
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| 7 | Midterm on 3/1 Covariance and its uses |
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| 8 | Central Limit Theorem Probability densities |
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| 9 | Transformations Joint Densities |
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| Spring Break |
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| 10 | Independent normal and gamma variables Moment generating functions and Chernoff bound |
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| 11 | MLE; Conditioning; MAP Estimates The beta and the binomial |
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| 12 | Prediction and Error Error Variance |
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| 13 | Random vectors; multivariate normal Correlation and simple regression |
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| 14 | Multiple regression I Multiple regression II |
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| 15 | RRR Week | |
| 16 | Final Exam | |