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    Ten Great Ideas about Chance

    by Persi Diaconis, Brian Skyrms


    eBook

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      ISBN-13: 9781400888283
    • Publisher: Princeton University Press
    • Publication date: 10/23/2017
    • Sold by: Barnes & Noble
    • Format: eBook
    • Pages: 272
    • Sales rank: 392,068
    • File size: 3 MB

    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.

    Table of Contents

    Preface ix
    Acknowledgments xi
    1 Measurement 1
    2 Judgment 22
    3 Psychology 48
    4 Frequency 62
    5 Mathematics 79
    6 Inverse Inference 100
    7 Unification 122
    8 Algorithmic Randomness 145
    9 Physical Chance 165
    10 Induction 190
    Appendix: Probability Tutorial 209
    Notes 225
    Annotated Select Bibliography 239
    Image Credits 247
    Index 249

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    A fascinating account of the breakthrough ideas that transformed probability and statistics

    In 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.

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    From the Publisher

    "A volume that should be on every scientist’s reading list."--Barb Kiser, Nature

    "Mathematically rigorous, yet also reasonably accessible; informative, yet fun and entertaining to read. Both students and faculty should find reading this to be a rewarding experience."--MAA Reviews

    "The audience is quite specific, but for them it will be a gem. . . . I would recommend this to any student studying or having studied anything statistics related at university."--Jonathan Shock, Mathemafrica

    "A very enriching journey. Your vision will be broadened assimilating all these issues and solutions as well as open problems from the early history of probability, game theory, financial markets, politics, thermodynamics, quantum theory and much much more."--Adhemar Bultheel, European Mathematical Society

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