Week 2 - Probability Review
Content for week of Monday, September 7, 2020–Friday, September 11, 2020
Overview
Welcome to Week 1! Our goal this week is to (1) help us sort out our varying technologies and workflows and (2) review some statistics! Basically, this is week 1 of a two-week mini-bootcamp to get us ready for the glorious world of regressions!
What you should do this week and the next week depends on your background:
Reading Guide
Chapter 2: Review of Probability
This is the material you should know, along with supports from Khan Academy ( ). Remember that you don’t need to memorize formulas!
- SW 2.1 Random Variables and Probability Distributions
- SW 2.2 Expected Values, Mean, and Variance
- You only need a general knowledge of kurtosis and skew.
- Transforming random variables
- SW 2.3 Two Random Variables
- Law of iterated expectations can be skimmed
- Make sure you’re good with key concept box 2.3!
- Combining random variables
- Law of iterated expectations can be skimmed
- SW 2.4 The Normal, Chi-Squared, Student t, and F distributions
- Normal distribution
and t-distributiononly. We won’t use chi-squared, and we’ll come back to F-distributions later. For any work we’ll be doing, our sample sizes will be greater than 100, so - Normal distributions and the empirical rule
- Normal distribution calculations
- Normal distribution
- SW 2.5 Random Sampling and the Distribution of the Sample Average
- SW 2.6 Large-sample approximations to sampling distributions
- Get that central limit theorem!
- Sampling distribution of a sample mean (relevant for 2.5 as well)
