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Week 1

Introduction

Week 3

Random Counts

Week 6

Reversing Markov Chains

Week 7

Midterm

Week 8

Variance and Covariance

Week 9

Continuous Distributions

Week 10

Working with Continuous Distributions

Week 11

The Normal and Gamma Families

Week 12

An Approach to Prediction

Week 13

Least Squares Prediction

Week 14

Regression

Week 15

WeekDateActivityContentReadings Assignment
1 Wed 1/17 Lecture 1 Probability: Axioms, Rules, Approximation Week 1 Guide
Ch 1: Fundamentals
Ch 2: Calculating Chances
HW 1
Thu 1/18 Discussion
Fri 1/19 Lab 1 Birthday Attack Lab 1
2 Mon 1/22 Lecture 2 Random Variables: Distributions, Conditioning, Equality Week 2 Guide
Ch 3: Random Variables
Ch 4: Relations Between Variables
Tue 1/23 HW 1 Due
Wed 1/24 Lecture 3 Symmetry and Collections of Events Ch 5: Collections of Events
HW 2
Thu 1/25 Discussion
Fri 1/26 Lab 2 Five-Card Poker Lab 2
3 Mon 1/29 Lecture 4 Binomial and Related Counts; the Poisson Limit Week 3 Guide
Ch 6: Random Counts
Tue 1/30 HW 2 Due
Wed 1/31 Lecture 5 Independence and Poissonization Ch 7: Poissonization
HW 3
Thu 2/1 Discussion
Fri 2/2 Lab 3 Total Variation Lab 3
4 Mon 2/5 Lecture 6 Expectation and Additivity Week 4 Guide
Ch 8: Expectation
Tue 2/6 HW 3 Due
Wed 2/7 Lecture 7 Finding Expectations by Conditioning Ch 9: Conditioning, Revisited
HW 4
Thu 2/8 Discussion
Fri 2/9 Lab 4 Expectations of Discrete Order Statistics Lab 4
5 Mon 2/12 Lecture 8 Long Run Behavior of Markov Chains Week 5 Guide
Ch 10: Markov Chains
Tue 2/13 HW 4 Due
Wed 2/14 Lecture 9 Reversibility Ch 11: Reversing Markov Chains
HW 5
Thu 2/15 Discussion
Fri 2/16 Lab 5 Uniform and Size Biased Permutations Lab 5
6 Mon 2/19 Holiday: No content Midterm Guide
Tue 2/20 HW 5 Due
Wed 2/21 Lecture 10 Markov Chain Monte Carlo
Thu 2/22 Discussion
Fri 2/23 Lab 6 Lab 6
7 Mon 2/26 Lecture 11 Midterm Review
Tue 2/27 HW 6 Due
Wed 2/28 Midterm
Thu 3/1 No Discussion
Fri 3/2 Lab 7 Lab 7
8 Mon 3/5 Lecture 12 SD: Tail Bounds, Least Squares
Tue 3/6 HW 7 Due
Wed 3/7 Lecture 13 Covariance and its Uses
Thu 3/8 Discussion
Fri 3/9 Lab 8 Lab 8
9 Mon 3/12 Lecture 14 Central Limit Theorem
Tue 3/13 HW 8 Due
Wed 3/14 Lecture 15 Probability Densities
Thu 3/15 Discussion
Fri 3/16 Lab 9 Lab 9
10 Mon 3/19 Lecture 16 Transformations
Tue 3/20 HW 9 Due
Wed 3/21 Lecture 17 Joint Densities; the Beta Family
Thu 3/22 Discussion
Fri 3/23 No lab
11 Mon 4/2 Lecture 18 Independent Normals; Maximum Likelihood
Tue 4/3 HW 10 Due
Wed 4/4 Lecture 19 Sums and the Gamma Family
Thu 4/5 Discussion
Fri 4/6 Lab 10 Lab 10
12 Mon 4/9 Lecture 20 Moment Generating Functions; Chernoff Bound
Tue 4/10 HW 11 Due
Wed 4/11 Lecture 21 Prior and Posterior Distributions; Beta-Binomial
Thu 4/12 Discussion
Fri 4/13 Lab 11 Lab 11
13 Mon 4/16 Lecture 22 Best Predictor
Tue 4/17 HW 12 Due
Wed 4/18 Lecture 23 Best Linear Predictor
Thu 4/19 Discussion
Fri 4/20 Lab 12 Lab 12
14 Mon 4/23 Lecture 24 Multivariate Normal
Tue 4/24 HW 13 Due
Wed 4/25 Lecture 25 Correlation and Regression
Thu 4/26 Discussion
Fri 4/27 Review Session
15 Fri 5/11 FINAL EXAM (3-6)