Part 1: Modeling variation and making statistical decisions

1: The Language of Statistical Decisions

2: The Language of Probability Models

3: Algorithms that generate probability models

4: Significance, Power, and $p$-values

Tell me more: Gerrymandering

Part 2: How to update your opinion based on new evidence

3: Conditional Probability and Independence

5: Bayesian methods

Tell me more: Vaccines

Tell me more: Counting

Problem Sets for Part 2

Part 3: Parameter estimation and interpretation

In this section, we strive for the standard communicated by this quote, adopted from Natasha Sarin’s interview on the Ezra Klein podcast.

Q: Is the glass half-empty or half full? A: This 8 ounce glass contains 4 ounces of water, plus or minus 0.03 ounces.

6: Z and the Central Limit Theorem; t and small sample means

7: Transformations of data and confidence intervals.

8: Comparisons of two sample populations.

Part 4: Correlation, Regression, and Prediction

9: Correlation (which does not imply causation!) and Regression