Read more
Klappentext This in-depth treatment of probability theory by a famous British statistician explores Keynesian principles and surveys such topics as Bayesian rationality, corroboration, hypothesis testing, and mathematical tools for induction and simplicity. 1983 edition. Inhaltsverzeichnis AcknowledgmentsIntroductionPart I. Bayesian Rationality1. Rational Decisions2. Twenty-seven Principles of Rationality3. 46656 Varieties of Bayesians4. The Bayesian Influence, or How to Sweep Subjectivism under the CarpetPart II. Probability5. Which Comes First, Probability or Statistics6. Kinds of Probability7. Sublective Probability as the Measure of a Non-measurable Set8. Random Thoughts about Randomness9. Some History of the Hierarchical Bayesian Methodology10. Dynamic Probability, Computer Chess, and the Measurement of KnowledgePart III . Corroboration, Hypothesis Testing, Induction, and Simplicity11. The White Shoe is a Red Herring12. The White Shoe qua Herring is Pink13. A Sublective Evaluation of Bode's Law and an "Objective" Test for Approximate Numerical Rationality14.Some Logic and History of Hypothesis Testing15. Explicativity, Corroboration, and the Relative Odds of HypothesisPart IV Information and Surprise16. The Appropriate Mathematical Tools for Describing and Measuring Uncertainty17. On the Principle of Total Evidence18.A Little Learning Can Be Dangerous19. The Probabilistic Explication of Information, Evidence, Surprise, Causality, Explanation, and Utility20. Is the Size of Our Galaxy Surprising?Part V. Causality and Explanation21. A Causal Calculus22. A Simplification in the "Causal Calculus"23. Explicativity: A Mathematical Theory of Explanations with Statistical ApplicationsReferencesBibliographySublect Index of the BibliographyName IndexSublect Index
