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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 10

Working with Continuous Distributions

Week 11

The Normal and Gamma Families

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 HW 6
Thu 2/22 Discussion
Fri 2/23 Lab 6 Code Breaking by MCMC 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 Board Game Night Lab 7
8 Mon 3/5 Lecture 12 SD: Tail Bounds, Least Squares Week 8 Prep Guide
Ch 12: Standard Deviation
Tue 3/6 HW 7 Due
Wed 3/7 Lecture 13 Covariance and its Uses Ch 13: Variance Via Covariance
HW 8
Thu 3/8 Discussion
Fri 3/9 Lab 8 Decisions Based on Ranks Lab 8
9 Mon 3/12 Lecture 14 Central Limit Theorem Week 9 Prep Guide
Ch 14: The Central Limit Theorem
Tue 3/13 HW 8 Due
Wed 3/14 Lecture 15 Probability Densities Ch 15: Continuous Distributions
HW 9
Thu 3/15 Discussion
Fri 3/16 Lab 9 Simulation and the CDF Lab 9
10 Mon 3/19 Lecture 16 Transformations Week 10 Prep Guide
Ch 16: Transformations
Tue 3/20 HW 9 Due
Wed 3/21 Lecture 17 Joint Densities; the Beta Family Ch 17: Joint Densities
HW 10
Thu 3/22 Discussion
Fri 3/23 No lab
11 Mon 4/2 Lecture 18 Independent Normal and Gamma Variables Week 11 Prep Guide
Ch 18: The Normal and Gamma Families
Tue 4/3 HW 10 Due
Wed 4/4 Lecture 19 Moment Generating Functions; Chernoff Bound Ch 19: Distributions of Sums
HW 11
Thu 4/5 Discussion
Fri 4/6 Lab 10 Introduction to Jointly Normal Vectors Lab 10
12 Mon 4/9 Lecture 20 MLE, Posterior Distributions, and MAP Estimates Week 12 Prep Guide
Ch 20: Approaches to Estimation
Tue 4/10 HW 11 Due
Wed 4/11 Lecture 21 Beta-Binomial Ch 21: The Beta and the Binomial
HW 12
Thu 4/12 Discussion
Fri 4/13 Lab 11 Chinese Restaurant Process, Part I Lab 11
13 Mon 4/16 Lecture 22 Prediction and Error Ch 22: Prediction
Tue 4/17 HW 12 Due
Wed 4/18 Lecture 23 Multivariate Normal Distribution Ch 23: Jointly Normal Random Variables
HW 13
Thu 4/19 Discussion
Fri 4/20 Lab 12 Chinese Restaurant Process, Part II Lab 12
14 Mon 4/23 Lecture 24 Correlation and Simple Regression
Tue 4/24 HW 13 Due
Wed 4/25 Lecture 25 Multiple Regression
Thu 4/26 Discussion
Fri 4/27 Review Session
15 Fri 5/11 FINAL EXAM (3-6)