The Handbook of Probability presents an equal balance of theory and direct applications in a non-technical, yet comprehensive format so that researchers of various backgrounds can use the reference either as a primer for understanding basic probability theory or as a more advanced research tool for specific projects requiring a deeper understanding or application of probability. The wide-ranging applications of probability presented make it useful for researchers who need to make interdisciplinary connections in their work, as well as professors who teach a range of students (social sciences, education, business, behavioral sciences, etc.) and need to bring probability into greater, concrete perspective for these students.
Foreword Background and Theory of Probability History of probability theory - Peter M. Lee Frequentist probability theory - Herwig Friedl, Siegfried Hormann Subjective and Other Probabilities - Igor Kopylov Paradoxes in probability theory - Nicholas Shackel Probability Theory in Research Methodology Probability theory in statistics - Tamas Rudas The Bayesian approach to statistics - Anthony O'Hagan Design of experiments - Mauro Gasparini , Maria Piera Rogantin Probability and causality - Michael E. Sobel Randomness and computation - Oded Goldreich Applications Time series analysis - Michael A. Lewis Survival analysis - Nancy Brandon Tuma Probabilistic sampling - Jeffrey M. Wooldridge Panel studies - Edward Frees, Jee-Seon Kim Probabilistic methods in surveys and official statistics - Vasja Vehovar, Matka Zaletel, Rudi Seljak Probabilistic models of measurement errors - Nick Longford Test development - Klaas Sijtsma, Wilco Emons Probabilistic Models of the Society/Simulation - Klaus G. Troitzsch Probabilistic network analysis - Philippa Pattison, Garry Robins Gambling - Charles Friedman Insurance pricing - Richard Derrig, Krzysztof Ostaszewski Credit scoring/rating - A. J. Feelders Investment portfolios and stock pricing - Craig G. Rennie Expert systems - George Luger, Chayan Chakrabarti Preface Advisory Board Part I: Background and Theory of Probability 1. History of Probability Theory - Peter M. Lee 2. Frequentist Probability Theory - Herwig Friedl and Siegfried Hormann 3. Subjective Probability - Igor Kopylov 4. Paradoxes in Probability Theory - Nicholas Shackel Part II: Probability Theory in Research Methodology 5. Probability Theory in Statistics - Tamas 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 Part III: Applications 10. Time-Series Analysis - Michael Anthony Lewis 11. Survival Analysis - Nancy Brandon Tuma 12. Probabilistic Sampling - Jeffrey M. Wooldridge 13. Panel Studies - Edward W. Frees and Jee-Seon Kim 14. Probabilistic Methods in Surveys and Offical Statistics - Vasja Vehovar, Matka Zaletel, and Rudi Seljak 15. Probabilistic 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. Probabilistic Simulation Models of Society - Klaus G. Troitzsch 18. Probabilistic Network Analysis - Philippa Pattison and Garry Robins 19. Gambling - Chas Friedman 20. Insurance - Richard A. Derrig and Krzysztof Ostaszewski 21. Credit Scoring - Ad Feelders 22. Investment Portfolios and Stock Pricing - Craig G. Rennie 23. Expert Systems - George Luger and Chayan Chakrabarti 24. Probability and Evidence - Julia Mortera and Philip Dawid 25. Probability in the Courtroom - Basil C. Bitas About the Editor About the Contributors Index
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