Index for the code and data for the book Regression and Other Stories

Below folders (ending /) point to the code folders in github, and .html -files point to pretty notebooks.


Code and data by chapters

1 Introduction

2 Data and measurement

3 Some basic methods in mathematics and probability

4 Generative models and statistical inference

5 Simulation

6 Background on regression modeling

7 Linear regression with a single predictor

8 Fitting regression models

9 Prediction and Bayesian inference

10 Linear regression with multiple predictors

11 Assumptions, diagnostics, and model evaluation

12 Transformations

13 Logistic regression

14 Working with logistic regression

15 Other generalized linear models

16 Design and sample size decisions

17 Poststratification and missing-data imputation

18 Causal inference basics and randomized experiments

19 Causal inference using regression on the treatment variable

20 Observational studies with all confounders assumed to be measured

21 More advanced topics in causal inference

22 Advanced regression and multilevel models

Appendix B


Code and data alphabetically