Pt. I. Background and theory of probabability.
1. History of probability theory / Peter M. Lee
2. Frequentist probability theory / Herwig Friedl and Siegfried Hörmann
3. Subjective probability / Igor Kopylov
4. Paradoxes in probability theory / Nicholas Shackel
Pt. II. Probability theory in research methodology.
5. Probability theory in statistics / Tamás Rudas
6. The Bayesian approach to statistics / Anthony O'Hagan
7. Design of experiments / Mauro Gasparini and Maria Piera Rogantin
8. Causation and causal inference : defining, identifying, and estimating causal effects / Michael Sobel
9. Randomness and computation / Oded Goldreich
10. Time-series analysis / Michael Anthony Lewis
11. Survival analysis / Nancy Brandon Tuma
12. Probabalistic sampling / Jeffrey M. Wooldridge
13. Panel studies / Edward W. Frees and Jee-Seon Kim
14. Probabalistic methods in surveys and official statistics / Vasja Vehovar, Makta Zaletel, and Rudi Seljak
15. Probabalistic models of measurement errors / Nicholas T. Longford
16. Statistical models for the development of psychological and educational tests / Klaas Sijtsma and Wilco H.M. Emons
17. Probabalistic simulation models of society / Klaus G. Troitzsch
18. Probabalistic network analysis / Philippa Pattison and Garry Robins
19. Gambling / Chas Friedman
20. Insurance / Richard A. Derrig and Krzysztof Ostaszewski
21. Credit scoring / Al Feelders
22. Investment portfolios and stock pricing / Craig G. Rennie
23. Expert systems / George Luger and Chayan Chakrabarti
24. Probability and evidence / Juia Mortera and Philip Dawid
25. Probability in the courtroom / Basil C. Bitas.
