Example: predicting the price of a house.15.6 “What variables should I include?”.Statistical vs. practical significance, revisited.15.2 Interactions of numerical and grouping variables.
Example 1: causal confusion in house prices.15.1 Numerical and grouping variables together.14.3 Models with multiple dummy variables.12.5 Example: labor market discrimination.The basic recipe of large-sample inference.10.2 The four steps of hypothesis testing.10.1 Example 1: did the Patriots cheat?.9.5 Bootstrapping usually, but not always, works.Bootstrap standard errors and confidence intervals.9.1 The bootstrap sampling distribution.
2.6 Importing data from the command line.Data Science in R: A Gentle Introduction.
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