Ten Great Ideas about Chance (eBook)

eBook Download: PDF
2017
272 Seiten
Princeton University Press (Verlag)
978-1-4008-8828-3 (ISBN)

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Ten Great Ideas about Chance - Persi Diaconis, Brian Skyrms
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A fascinating account of the breakthrough ideas that transformed probability and statisticsIn the sixteenth and seventeenth centuries, gamblers and mathematicians transformed the idea of chance from a mystery into the discipline of probability, setting the stage for a series of breakthroughs that enabled or transformed innumerable fields, from gambling, mathematics, statistics, economics, and finance to physics and computer science. This book tells the story of ten great ideas about chance and the thinkers who developed them, tracing the philosophical implications of these ideas as well as their mathematical impact.Persi Diaconis and Brian Skyrms begin with Gerolamo Cardano, a sixteenth-century physician, mathematician, and professional gambler who helped develop the idea that chance actually can be measured. They describe how later thinkers showed how the judgment of chance also can be measured, how frequency is related to chance, and how chance, judgment, and frequency could be unified. Diaconis and Skyrms explain how Thomas Bayes laid the foundation of modern statistics, and they explore David Hume's problem of induction, Andrey Kolmogorov's general mathematical framework for probability, the application of computability to chance, and why chance is essential to modern physics. A final idea-that we are psychologically predisposed to error when judging chance-is taken up through the work of Daniel Kahneman and Amos Tversky.Complete with a brief probability refresher, Ten Great Ideas about Chance is certain to be a hit with anyone who wants to understand the secrets of probability and how they were discovered.

Persi Diaconis is the Mary V. Sunseri Professor of Statistics and Mathematics at Stanford University and the coauthor of Magical Mathematics: The Mathematical Ideas That Animate Great Magic Tricks (Princeton). Brian Skyrms is Distinguished Professor in the Department of Logic and Philosophy at the University of California, Irvine, and Professor of Philosophy at Stanford University. His books include From Zeno to Arbitrage.

Zusatzinfo 25 halftones. 19 line illus. 8 tables.
Verlagsort Princeton
Sprache englisch
Themenwelt Mathematik / Informatik Mathematik
Schlagworte Accuracy and precision • Algorithmic Probability • Almost surely • An Essay towards solving a Problem in the Doctrine of Chances • Atomism • Axiom • Base rate • Bayesian • Bayesian probability • Bayesian Statistics • Bayes' Theorem • Big O notation • birthday problem • Brian Skyrms • Bruno de Finetti • Calculation • Cardinal utility • central limit theorem • chaos theory • Chi-squared test • Classical physics • Continuum Hypothesis • Counting • David Aldous • De Finetti's theorem • dutch book • Dutch Book Theorem • Entscheidungsproblem • Equiprobability • ergodic hypothesis • Ergodicity • ergodic process • ergodic theory • Ernst Zermelo • Error Term • Event (probability theory) • Expected utility hypothesis • expected value • Fair coin • fair division • Frequentist probability • greedy algorithm • Heuristic • H-Theorem • ideal gas • ideal gas law • idealization • inference • Infimum and supremum • law of large numbers • Law of total probability • Likelihood-ratio test • logarithm • Logical conjunction • Logical disjunction • Magic Square • Martingale (probability theory) • Monte Carlo Method • Mutual exclusivity • Natural number • New riddle of induction • Nontransitive dice • Objective Probability • Outcome (probability) • Prime number • Prior probability • Probabilism • Probability • probability and statistics • Probability Distribution • Probability interpretations • probability measure • Probability space • Probability Theory • Pure Mathematics • p-value • quantum mechanics • Quantum probability • random number generation • random sequence • Random Variable • Rational number • Real gas • real number • Richard Jeffrey • scientific notation • Scoring rule • Significant figures • Special case • Statistical Inference • Statistical Mechanics • Statistical Physics • Statistical Science • statistical significance • Toy model • Turing Machine • universal turing machine • Utilitarianism • Weighted arithmetic mean • With high probability
ISBN-10 1-4008-8828-X / 140088828X
ISBN-13 978-1-4008-8828-3 / 9781400888283
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