How To Gamble If You Must

Author: Lester E. Dubins
Editor: Courier Corporation
ISBN: 0486780643
Size: 11,44 MB
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This classic of advanced statistics is geared toward graduate-level readers and uses the concepts of gambling to develop important ideas in probability theory. The authors have distilled the essence of many years' research into a dozen concise chapters. "Strongly recommended" by the Journal of the American Statistical Association upon its initial publication, this revised and updated edition features contributions from two well-known statisticians that include a new Preface, updated references, and findings from recent research. Following an introductory chapter, the book formulates the gambler's problem and discusses gambling strategies. Succeeding chapters explore the properties associated with casinos and certain measures of subfairness. Concluding chapters relate the scope of the gambler's problems to more general mathematical ideas, including dynamic programming, Bayesian statistics, and stochastic processes. Dover (2014) revised and updated republication of the 1976 Dover edition entitled Inequalities for Stochastic Processes. See every Dover book in print at www.doverpublications.com

Inequalities For Stochastic Processes

Author: Lester E. Dubins
Editor:
ISBN:
Size: 14,36 MB
Format: PDF
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Gladiators Pirates And Games Of Trust

Author: Haim Shapira
Editor: Watkins Media Limited
ISBN: 178678064X
Size: 15,34 MB
Format: PDF, ePub
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An accessible, light-hearted exploration into Game Theory. Haim Shapira describes what it is, why it is important and how it can help us in our daily lives. This book provides many humorous anecdotes and insightful examples of how our daily lives are affected by Game Theory. Game Theory is the mathematical formalization of interactive decision-making – it assumes that each player's goal is to maximize his/her benefit, whatever it may be. Players may be friends, foes, political parties, states, or any entity that behaves interactively, whether collectively or individually. One of the problems with game analysis is the fact that, as a player, it’s very hard to know what would benefit each of the other players; some of us are not even clear about our own goals or what might actually benefit us. Haim Shapira uses multiple examples to explain what Game Theory is and how the different interactions between decision-makers can play out. In this book you will: • Meet the Nobel Laureate John F Nash and familiarize yourself with his celebrated equilibrium • Learn the basic ideas of the art of negotiation • Visit the gladiators’ ring and apply for a coaching position • Build an airport and divide inheritance • Issue ultimatums and learn to trust

The Doctrine Of Chances

Author: Stewart N. Ethier
Editor: Springer Science & Business Media
ISBN: 9783540787839
Size: 20,92 MB
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Three centuries ago Montmort and De Moivre published two books on probability theory emphasizing its most important application at that time, games of chance. This book, on the probabilistic aspects of gambling, is a modern version of those classics.

The Perfect Bet

Author: Adam Kucharski
Editor: Profile Books
ISBN: 178283205X
Size: 16,24 MB
Format: PDF, ePub
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Gamblers have been trying to figure out how to game the system since our ancestors first made wagers over dice fashioned from knucklebones: in revolutionary Paris, the 'martingale' strategy was rumoured to lead to foolproof success at roulette ; today, professional gamblers are using cutting-edge techniques to tilt the odds in their favour. Science is giving us the competitive edge over opponents, casinos and bookmakers. But is there such a thing as a perfect bet? The Perfect Bet looks beyond probability and statistics to examine how wagers have inspired a plethora of new disciplines - spanning chaos theory, machine learning and game theory - which are not just revolutionising gambling, but changing our fundamental notions about chance, randomness and luck. Explaining why poker is gaming's last bastion of human superiority over AI, how methods originally developed for the US nuclear programme are helping pundits predict sports results and why a new breed of algorithms are losing banks millions, The Perfect Bet has the inside track on any wager you'd care to place.

Comparative Statistical Inference

Author: Vic Barnett
Editor: John Wiley & Sons
ISBN: 9780471976431
Size: 16,57 MB
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This fully updated and revised third edition, presents a wide ranging, balanced account of the fundamental issues across the full spectrum of inference and decision-making. Much has happened in this field since the second edition was published: for example, Bayesian inferential procedures have not only gained acceptance but are often the preferred methodology. This book will be welcomed by both the student and practising statistician wishing to study at a fairly elementary level, the basic conceptual and interpretative distinctions between the different approaches, how they interrelate, what assumptions they are based on, and the practical implications of such distinctions. As in earlier editions, the material is set in a historical context to more powerfully illustrate the ideas and concepts. Includes fully updated and revised material from the successful second edition Recent changes in emphasis, principle and methodology are carefully explained and evaluated Discusses all recent major developments Particular attention is given to the nature and importance of basic concepts (probability, utility, likelihood etc) Includes extensive references and bibliography Written by a well-known and respected author, the essence of this successful book remains unchanged providing the reader with a thorough explanation of the many approaches to inference and decision making.

Modeling Techniques In Predictive Analytics With Python And R

Author: Thomas W. Miller
Editor: FT Press
ISBN: 013389214X
Size: 19,67 MB
Format: PDF, Kindle
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Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Theory Of Charges

Author: K.P.S. Bhaskara Rao
Editor: Academic Press
ISBN: 0080874282
Size: 11,59 MB
Format: PDF, ePub
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Theory of Charges

Real Analysis And Probability

Author: Robert B. Ash
Editor: Academic Press
ISBN: 1483191427
Size: 18,32 MB
Format: PDF, Mobi
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Real Analysis and Probability provides the background in real analysis needed for the study of probability. Topics covered range from measure and integration theory to functional analysis and basic concepts of probability. The interplay between measure theory and topology is also discussed, along with conditional probability and expectation, the central limit theorem, and strong laws of large numbers with respect to martingale theory. Comprised of eight chapters, this volume begins with an overview of the basic concepts of the theory of measure and integration, followed by a presentation of various applications of the basic integration theory. The reader is then introduced to functional analysis, with emphasis on structures that can be defined on vector spaces. Subsequent chapters focus on the connection between measure theory and topology; basic concepts of probability; and conditional probability and expectation. Strong laws of large numbers are also examined, first from the classical viewpoint, and then via martingale theory. The final chapter is devoted to the one-dimensional central limit problem, paying particular attention to the fundamental role of Prokhorov's weak compactness theorem. This book is intended primarily for students taking a graduate course in probability.

Measure Integration And Functional Analysis

Author: Robert B. Ash
Editor: Academic Press
ISBN: 1483265102
Size: 12,21 MB
Format: PDF
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Measure, Integration, and Functional Analysis deals with the mathematical concepts of measure, integration, and functional analysis. The fundamentals of measure and integration theory are discussed, along with the interplay between measure theory and topology. Comprised of four chapters, this book begins with an overview of the basic concepts of the theory of measure and integration as a prelude to the study of probability, harmonic analysis, linear space theory, and other areas of mathematics. The reader is then introduced to a variety of applications of the basic integration theory developed in the previous chapter, with particular reference to the Radon-Nikodym theorem. The third chapter is devoted to functional analysis, with emphasis on various structures that can be defined on vector spaces. The final chapter considers the connection between measure theory and topology and looks at a result that is a companion to the monotone class theorem, together with the Daniell integral and measures on topological spaces. The book concludes with an assessment of measures on uncountably infinite product spaces and the weak convergence of measures. This book is intended for mathematics majors, most likely seniors or beginning graduate students, and students of engineering and physics who use measure theory or functional analysis in their work.