Foundations of Probability with Applications
Selected Papers 1974–1995
£40.99
Part of Cambridge Studies in Probability, Induction and Decision Theory
- Authors:
- Patrick Suppes, Stanford University, California
- Mario Zanotti, Computer Curriculum Corporation, California
- Date Published: February 1997
- availability: Available
- format: Paperback
- isbn: 9780521568357
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This is an important collection of essays dealing with the foundations of probability that will be of value to philosophers of science, mathematicians, statisticians, psychologists and educationalists. The collection falls into three parts. Part I comprises five essays on the axiomatic foundations of probability. Part II contains seven articles on probabilistic causality and quantum mechanics, with an emphasis on the existence of hidden variables. The third part consists of a single extended essay applying probabilistic theories of learning to practical questions of education: it incorporates extensive data analysis. Patrick Suppes is one of the world's foremost philosophers in the area of probability, and has made many contributions to both the theoretical and practical side of education. The statistician Mario Zanotti is a long-time collaborator.
Read more- Suppes is the major selling point - internationally famous philosopher of science
- Major collection of papers on probability that will interest both philosophers and mathematicians
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×Product details
- Date Published: February 1997
- format: Paperback
- isbn: 9780521568357
- length: 208 pages
- dimensions: 230 x 153 x 13 mm
- weight: 0.294kg
- contains: 27 b/w illus.
- availability: Available
Table of Contents
Part I. Foundations of Probability:
1. Necessary and sufficient conditions for existence of a unique measure strictly agreeing with a qualititative probability ordering
2. Necessary and sufficient qualitative axioms for conditional probability
3. On using random relations to generate upper and lower probabilities
4. Conditions on upper and lower probabilities to imply probabilities
5. Qualitative axioms for random-variable representation of extensive quantifiers
Part II. Causality and Quantum Mechanics:
6. Stochastic incompleteness of quantum mechanics
7. On the determinism of hidden variable theories with strict correlation and conditional statistical independence of observables
8. A new proof of the impossibility of hidden variables using the principles of exchangeability and identity of conditional distribution
9. When are probabilistic explanations possible?
10. Causality and symmetry
11. New Bell-type inequalities for N>4 necessary for existence of a hidden variable
12. Existence of hidden variables having only upper probabilities
Part III. Applications in Education:
13. Mastery learning of elementary mathematics: theory and data.
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