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8/24 - Welcome to Data 88S Fall 2022!

Week 0 Overview

Getting Started

Week 1

Course Introduction and Chapter 1

Week 2

Intersections and Conditioning

Week 3

Random Variables

Week 4

Random Counts, Exponential Approximations, and the (Hyper)geometric Distributions

Week 5

Poisson, Expectation, and Additivity

Week 6

Unbiased Estimators, Expectation by Conditioning

Week 7

Standard Deviation and Variance

WeekDateContentNotes & Assignments
1 Course introduction; fundamentals, exact calculations, and bounds
Friday discussion problems: Ch. 1 Ex. 1
Homework 1 (Due 8/30 at 4pm)
2 The rules; intersections and conditioning
Updating chances; independence
Wednesday discussion problems: Ch. 1 Ex. 2; Ch. 2 Ex. 5, 10, 12
Friday discussion problems: Ch. 2 Ex. 4, 11, 7, 6
Homework 2 (Due 9/6 at 4pm)
3 Random variables
Quiz 1 on Wed 9/7
Random counts: binomial
Friday discussion problems: Ch. 3 Ex. 1, 2, 3cd
Homework 3 (Due 9/13 at 4pm)
4 Random counts: hypergeometric
Exponential approximations; geometric
Wednesday discussion problems: Ch. 3 Ex. 6, 9, 10; Ch. 4 Ex. 2
Friday discussion problems: Ch. 4 Ex. 4, 5, 6
Homework 4 (Due 9/20 at 4pm)
5 Law of small numbers: Poisson
Quiz 2 on Wed 9/21
Expectation and additivity
Friday discussion problems: Ch. 5 Ex. 1, 4, 7
Homework 5 (due 9/27 at 4pm)
6 Unbiased estimators
Expectation by conditioning
Homework 6 (due 10/4 at 4pm)
7 Standard deviation; tail bounds
Variance and additivity: binomial and hypergeometric
Homework 7 (due 10/10 at 5pm (note that this is MONDAY))
8 Midterm on Tue 10/11
Large samples: law of large numbers
9 Central Limit Theorem
CLT and confidence intervals
10 Testing hypotheses
Probability density
11 Expectation and variance revisited
The exponential distribution
12 The normal distribution
Quiz 3 on Wed 11/9
Estimation: bias and variance
13 Correlation and the regression line
Regression effect and regression fallacy
14 Error in regression
15 Inference in regression
Conclusion