Subject Index

Chapters in this book

1. Frontmatter I
2. Preface V
3. Contents VII
4. Chapter 1 Data Science in Social Research 1
5. Part I: Description, Explanation, Prediction
6. Chapter 2 Descriptive Inference 19
7. Chapter 3 Causal Inference 50
8. Part II: Using R
9. Chapter 4 Data Management in R 87
10. Chapter 5 R Graphics 144
11. Part III: Statistical Methods for Prediction, Classification, Text Analytics
12. Chapter 6 Linear Models 173
13. Chapter 7 Goodness of Fit and Predictive Power of a Linear Model 194
14. Chapter 8 Regression Diagnostics and Corrective Measures 229
15. Chapter 9 Linear Mixed Models 268
16. Chapter 10 Nonlinear Relations 286
17. Chapter 11 Classification 324
18. Chapter 12 Statistical Learning 359
19. Chapter 13 Natural Language Processing 395
20. References
21. R Libraries Used
22. About the Authors
23. Subject Index