Table of Contents

Acknowledgments Introduction Part I. Bayesian Rationality 1. Rational Decisions 2. Twenty-seven Principles of Rationality 3. 46656 Varieties of Bayesians 4. The Bayesian Influence, or How to Sweep Subjectivism under the Carpet Part II. Probability 5. Which Comes First, Probability or Statistics 6. Kinds of Probability 7. Sublective Probability as the Measure of a Non-measurable Set 8. Random Thoughts about Randomness 9. Some History of the Hierarchical Bayesian Methodology 10. Dynamic Probability, Computer Chess, and the Measurement of Knowledge Part III . Corroboration, Hypothesis Testing, Induction, and Simplicity 11. The White Shoe is a Red Herring 12. The White Shoe qua Herring is Pink 13. A Sublective Evaluation of Bode's Law and an "Objective" Test for Approximate Numerical Rationality 14.Some Logic and History of Hypothesis Testing 15. Explicativity, Corroboration, and the Relative Odds of Hypothesis Part IV Information and Surprise 16. The Appropriate Mathematical Tools for Describing and Measuring Uncertainty 17. On the Principle of Total Evidence 18.A Little Learning Can Be Dangerous 19. The Probabilistic Explication of Information, Evidence, Surprise, Causality, Explanation, and Utility 20. Is the Size of Our Galaxy Surprising? Part V. Causality and Explanation 21. A Causal Calculus 22. A Simplification in the "Causal Calculus" 23. Explicativity: A Mathematical Theory of Explanations with Statistical Applications References Bibliography Sublect Index of the Bibliography Name Index Sublect Index

About the Author

Under the supervision of Alan Turing, Irving J. Good worked with the Bletchley Park cryptographers who cracked the German Enigma code. A prolific author of technical papers, Good was Professor of Statistics at Virginia Tech from 1969 until his retirement in 1994.