Class Schedule and HW Assignments
M = Morin's Probability for the Enthusiastic Beginner
GS = Grinstead and Snell's Introduction to Probability
| Week | Date | Topics | Sections | Practice Problems (don't turn in) |
|
|---|---|---|---|---|---|
| 1 | 6/22 | Course Introduction; What is Probability?; Introduction to Counting |
M: 1.1-1.2 GS: 3.1-3.2 |
M, p.36: 1.1, 1.2 GS, p.88: 1, 2, 5, 12, 13 |
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| 2 | 6/25 | Ordered and Unordered Sets | M: 1.3-1.6 | M, p.36: 1.3, 1.6 | |
| 6/26(x) | Set Theory and Proofs | Reading | from reading: p.12: 1 p.20: 1, 2 |
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| 6/27 | Induction; Binomial and Multinomial Coefficients | M: 1.8; reading (above) |
M, p.36: 1.7, 1.8, 1.9, 1.15 | ||
| 6/29 | Stars and Bars; License Plate Problems | M: 1.7, 1.9 | M, p.36: 1.11, 1.14 | ||
| Homework Due 7/6 (Solutions) | |||||
| 3 | 7/2 | Independence and Conditional Probability | M: 2.1-2.2 | M, p.109: 2.1, 2.4, 2.7 | |
| 7/3(x) | More on Conditional Probability; Disjoint Events | M: 2.2-2.3 | M, p.109: 2.9, 2.13 | ||
| 7/6 | Bayes' Theorem; Classical Probability Problems | M: 2.4-5 |
M, p.109: 2.14, 2.15, 2.22 | ||
| Homework Due 7/11 (Solutions) | |||||
| Exam 1 Practice Problems | GS p.88: #3, 7, 13, 14, 15 GS p.113: #8, 9, 16, 17, 19, 20, 35 GS p.150: #1, 2, 3, 4, 5, 9, 14, 18 |
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| 4 | 7/9 | Midterm Review | |||
| 7/11 | The R Programming Language | Install R AND Install RStudio |
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| 7/13 | Intro to Discrete Random Variables and Probability Distributions; Expected Value |
M: 4.1, 4.4-5, 4.6.1, 3.1 GS: 1.2 |
M, p.165: 3.3 | ||
| Homework Due 7/18 (Solutions) |
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| 5 | 7/16 | (Discrete) Expected Value and Games | M: 3.1 | M, p.165: 3.2, 3.4-5 | |
| 7/17(x) | R Practice (optional) | ||||
| 7/18 | (Discrete) Variance and Standard Deviation | M: 3.2-3 | M, p.165: 3.6, 3.7, 3.8 | ||
| 7/20 | Hypergeometric and Poisson Distributions | M: 4.7 | M, p.222: (4.5,) 4.13, 4.16, 4.17 | ||
| Homework Due 7/25 (TeX) (Solutions) |
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| Discrete Distributions Practice Problems | GS p.197: #1, 6, 7, 8, 13, 14, 16, 18, 21 | ||||
| Expected Value Practice Problems | GS p.246: #1, 2, 3, 4, 6, 8, 16, 23 | ||||
| Variance Practice Problems | GS p.263: #1, 3, 4, 7, 9, 10, 12, 23 | ||||
| 6 | 7/23 | Poisson Approximation of the Binomial Distribution; Continuous Distributions: Uniform |
GS: 5.1 M: 4.2-4.3 |
GS, p.197: #13, 14, 16 | |
| 7/25 | Continuous Expected Value and Variance; The Exponential Distribution |
GS: 6.3 M: 4.6, 4.8 |
GS, p.277: #1, 2, 3, 4 | ||
| 7/27 | The Exponential and Normal Distributions | GS: 5.2 M: 4.8 |
GS, p.209: #25-30 (M, p.222: 4.22-23) |
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| Homework Due 8/1 (TeX) (Solutions) |
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| 7 | 7/30 | Inequalities of Markov and Chebyshev; The Weak Law of Large Numbers |
GS 8.1-8.2 Class Notes |
GS, p.312: #5-8 GS, p.320: #2, 4, 5 |
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| 8/1 | Midterm Review | ||||
| 8/3 | Convolutions | GS 7.1-7.2 | GS, p.289: #2, 3, 5; GS, p.300: #2-5 |
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| 8 | 8/6 | The Central Limit Theorem | GS 9.1 | GS, p.338: #1-6 | |
| 8/8 | The Central Limit Theorem | GS 9.2-3 | GS p.352: #1, 3-7 GS p.361: #4, 5, 9 |
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| 8/10 | Introduction to Markov Chains | GS 11.1 | GS p.413: #2, 4, 5, 7, 11 | ||
| Homework Due 8/15 (TeX) (Solutions) |
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| 9 | 8/13 | Absorbing Markov Chains | GS 11.2 | GS p.422: #1, 2, 3, 5 | |
| 8/15 | Absorbing Markov Chains II; Ergodic and Regular Markov Chains |
GS 11.2-3 | GS p.422: #6, 9 GS p.442: #1, 3 |
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| 8/17 | Ergodic and Regular Markov Chains II | GS 11.3 | GS p.442: #5, 12, 14, 24 | ||
| Homework Due 8/22 (TeX) | |||||
| 10 | 8/20 | Class Cancelled | |||
| 8/22 | Final Review | ||||
Important Dates
| Date | Event |
|---|---|
| Friday, June 22: | First lecture |
| Tuesday, July 10: | Midterm Exam 1 (4:30-6:30 pm, Kemeny 007) |
| Monday, July 23: | Lab Assignment 1 due in class |
| Thursday, August 2: | Midterm Exam 2 (4:30-6:30 pm, Kemeny 007) |
| Tuesday, August 7: | Final day to withdraw from the course |
| Friday, August 10: | Lab Assignment 2 due in class |
| Wednesday, August 22: | Final lecture |
| Saturday, August 25: | Final Exam (8-11 am, Kemeny 007) |