Instructor: Nadia Lafrenière
Course on canvas.dartmouth.edu.⇗
Day-by-day Syllabus
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Sections of the book |
Brief Description - Course content |
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Week 1 |
1.1, 1.2, 2.1 |
Discrete probability distributions, simulation of continuous probabilities. |
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Week 2 |
2.2, 3.1, 3.2 |
Continuous probability distributions, Combinatorics |
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Week 3 |
3.3, 4.1, 4.2 |
Applications: Card shuffling. Conditional probability. |
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Week 4 |
4.3, 5.1, 5.2 |
Paradoxes. Distributions and Densities. End of the content for Midterm. |
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Week 5 |
6.1, 6.2 |
Expected value and variance. No x-hour (Anna and Nadia will be available for questions). Friday's class replaced with exam, at 8 am. |
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Week 6 |
6.3, 7.1, 7.2 |
Expected value and variance for continuous random variables. Sums of random variables. |
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Week 7 |
8.1, 8.2, 9.1 |
Law of large numbers and Central Limit Theorem. |
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Week 8 |
9.2, 9.3, 11.1 |
Central Limit Theorem (continued) and intro to Markov chains. |
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Week 9 |
11.2, 11.3, 12.2 |
Final project presentations |
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Week 10 |
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Monday: No class, Memorial day. Final project presentations Final exam on June 2 (3 pm). |