Statistical Rethinking, 2nd Edition

Table of contents

1. Cover
2. Half Title
3. Series Page
4. Title Page
5. Copyright Page
6. Table of Contents
7. Preface to the Second Edition
8. Preface
   1. Audience
   2. Teaching strategy
   3. How to use this book
   4. Installing the rethinking R package
   5. Acknowledgments
9. Chapter 1. The Golem of Prague
   1. 1.1. Statistical golems
   2. 1.2. Statistical rethinking
   3. 1.3. Tools for golem engineering
   4. 1.4. Summary
10. Chapter 2. Small Worlds and Large Worlds
    1. 2.1. The garden of forking data
    2. 2.2. Building a model
    3. 2.3. Components of the model
    4. 2.4. Making the model go
    5. 2.5. Summary
    6. 2.6. Practice
11. Chapter 3. Sampling the Imaginary
    1. 3.1. Sampling from a grid-approximate posterior
    2. 3.2. Sampling to summarize
    3. 3.3. Sampling to simulate prediction
    4. 3.4. Summary
    5. 3.5. Practice
12. Chapter 4. Geocentric Models
    1. 4.1. Why normal distributions are normal
    2. 4.2. A language for describing models
    3. 4.3. Gaussian model of height
    4. 4.4. Linear prediction
    5. 4.5. Curves from lines
    6. 4.6. Summary
    7. 4.7. Practice
13. Chapter 5. The Many Variables & The Spurious Waffles
    1. 5.1. Spurious association
    2. 5.2. Masked relationship
    3. 5.3. Categorical variables
    4. 5.4. Summary
    5. 5.5. Practice
14. Chapter 6. The Haunted DAG & The Causal Terror
    1. 6.1. Multicollinearity
    2. 6.2. Post-treatment bias
    3. 6.3. Collider bias
    4. 6.4. Confronting confounding
    5. 6.5. Summary
    6. 6.6. Practice
15. Chapter 7. Ulysses’ Compass
    1. 7.1. The problem with parameters
    2. 7.2. Entropy and accuracy
    3. 7.3. Golem taming: regularization
    4. 7.4. Predicting predictive accuracy
    5. 7.5. Model comparison
    6. 7.6. Summary
    7. 7.7. Practice
16. Chapter 8. Conditional Manatees
    1. 8.1. Building an interaction
    2. 8.2. Symmetry of interactions
    3. 8.3. Continuous interactions
    4. 8.4. Summary
    5. 8.5. Practice
17. Chapter 9. Markov Chain Monte Carlo
    1. 9.1. Good King Markov and his island kingdom
    2. 9.2. Metropolis algorithms
    3. 9.3. Hamiltonian Monte Carlo
    4. 9.4. Easy HMC: ulam
    5. 9.5. Care and feeding of your Markov chain
    6. 9.6. Summary
    7. 9.7. Practice
18. Chapter 10. Big Entropy and the Generalized Linear Model
    1. 10.1. Maximum entropy
    2. 10.2. Generalized linear models
    3. 10.3. Maximum entropy priors
    4. 10.4. Summary
19. Chapter 11. God Spiked the Integers
    1. 11.1. Binomial regression
    2. 11.2. Poisson regression
    3. 11.3. Multinomial and categorical models
    4. 11.4. Summary
    5. 11.5. Practice
20. Chapter 12. Monsters and Mixtures
    1. 12.1. Over-dispersed counts
    2. 12.2. Zero-inflated outcomes
    3. 12.3. Ordered categorical outcomes
    4. 12.4. Ordered categorical predictors
    5. 12.5. Summary
    6. 12.6. Practice
21. Chapter 13. Models With Memory
    1. 13.1. Example: Multilevel tadpoles
    2. 13.2. Varying effects and the underfitting/overfitting trade-off
    3. 13.3. More than one type of cluster
    4. 13.4. Divergent transitions and non-centered priors
    5. 13.5. Multilevel posterior predictions
    6. 13.6. Summary
    7. 13.7. Practice
22. Chapter 14. Adventures in Covariance
    1. 14.1. Varying slopes by construction
    2. 14.2. Advanced varying slopes
    3. 14.3. Instruments and causal designs
    4. 14.4. Social relations as correlated varying effects
    5. 14.5. Continuous categories and the Gaussian process
    6. 14.6. Summary
    7. 14.7. Practice
23. Chapter 15. Missing Data and Other Opportunities
    1. 15.1. Measurement error
    2. 15.2. Missing data
    3. 15.3. Categorical errors and discrete absences
    4. 15.4. Summary
    5. 15.5. Practice
24. Chapter 16. Generalized Linear Madness
    1. 16.1. Geometric people
    2. 16.2. Hidden minds and observed behavior
    3. 16.3. Ordinary differential nut cracking
    4. 16.4. Population dynamics
    5. 16.5. Summary
    6. 16.6. Practice
25. Chapter 17. Horoscopes
26. Endnotes
27. Bibliography
28. Citation index
29. Topic index