This book presents not only the mathematical concept of probability, but also its philosophical aspects, the relativity of probability and its applications and even the psychology of probability. All explanations are made in a comprehensible manner and are supported with suggestive examples from nature and daily life, and even with challenging math paradoxes. (Mathematics)

A comprehensive introduction to statistics that teaches the fundamentals with real-life scenarios, and covers histograms, quartiles, probability, Bayes' theorem, predictions, approximations, random samples, and related topics.

A visual reference to the mathematics of sports.

How do sportsbooks make their lines? Which types of bets are the best? Can you beat the house? The Logic Of Sports Betting answers all these questions and more with a dash of humor and a whole lot of real talk about how it all works. Peek behind the counter and learn how sportsbooks operate. Combine that insider knowledge with why-didn't-I-think-of-that sports betting logic, and you have the winning formula. Ed Miller is a best-selling (over 300,000 copies sold) author of books on poker and gambling. This is his first book on sports betting, but maybe his favorite book to write so far. Matthew Davidow is a sports modeler, using proprietary methods to beat major sports betting markets for over 15 years, and co-founding two leading private sports analytics firms along the way. What people are saying about The Logic Of Sports Betting "Matt and Ed are two of the smartest minds in sports betting." - Rufus Peabody, professional sports bettor "As a sportsbook employee for 30-plus years, I find it difficult to read or watch anything about sports betting. But I could not put The Logic Of Sports Betting down. It's that good." - Robert Walker, Las Vegas bookmaker

`There are few people who can write about research methods in a lively and engaging way, but Miles and Banyard are amongst them. As well as being an exceptionally clear introduction to research methods, it is full of amusing asides and anecdotes that make you want to read more. A hugely enjoyable book′ - Dr Andy Field, University of Sussex Understanding and Using Statistics in Psychology takes the fear out of psychological statistics to help students understand why statistics are carried out, how to choose the best test and how to carry out the tests and understand them. Taking a non-technical approach, it encourages the reader to understand why a particular test is being used and what the results mean in the context of a psychological study, focusing on meaning and understanding rather than mindless numerical calculation. Key features include: - A light and accessible style - Descriptions of the most commonly used statistical tests and the principles that underlie them - Real world examples to aid the understanding of why statistics are valuable - Boxes on common errors, tips and quotes - Test yourself questions The perfect introductory resource, Understanding and Using Statistics in Psychology will guide any student new to statistics effortlessly through the process of test selection and analysis.

Does God exist? This is probably the most debated question in the history of mankind. Scholars, scientists, and philosophers have spent their lifetimes trying to prove or disprove the existence of God, only to have their theories crucified by other scholars, scientists, and philosophers. Where the debate breaks down is in the ambiguities and colloquialisms of language. But, by using a universal, unambiguous language—namely, mathematics—can this question finally be answered definitively? That’s what Dr. Stephen Unwin attempts to do in this riveting, accessible, and witty book, The Probability of God. At its core, this groundbreaking book reveals how a math equation developed more than 200 years ago by noted European philosopher Thomas Bayes can be used to calculate the probability that God exists. The equation itself is much more complicated than a simple coin toss (heads, He’s up there running the show; tails, He’s not). Yet Dr. Unwin writes with a clarity that makes his mathematical proof easy for even the nonmathematician to understand and a verve that makes his book a delight to read. Leading you carefully through each step in his argument, he demonstrates in the end that God does indeed exist. Whether you’re a devout believer and agree with Dr. Unwin’s proof or are unsure about all things divine, you will find this provocative book enlightening and engaging. “One of the most innovative works [in the science and religion movement] is The Probability of God...An entertaining exercise in thinking.”—Michael Shermer, Scientific American “Unwin’s book [is] peppered with wry, self-deprecating humor that makes the scientific discussions more accessible...Spiritually inspiring.”--Chicago Sun Times “A pleasantly breezy account of some complicated matters well worth learning about.”--Philadelphia Inquirer “One of the best things about the book is its humor.”--Cleveland Plain Dealer “In a book that is surprisingly lighthearted and funny, Unwin manages to pack in a lot of facts about science and philosophy.”--Salt Lake Tribune

John Walsh, one of the great masters of the subject, has written a superb book on probability. It covers at a leisurely pace all the important topics that students need to know, and provides excellent examples. I regret his book was not available when I taught such a course myself, a few years ago. —Ioannis Karatzas, Columbia University In this wonderful book, John Walsh presents a panoramic view of Probability Theory, starting from basic facts on mean, median and mode, continuing with an excellent account of Markov chains and martingales, and culminating with Brownian motion. Throughout, the author's personal style is apparent; he manages to combine rigor with an emphasis on the key ideas so the reader never loses sight of the forest by being surrounded by too many trees. As noted in the preface, “To teach a course with pleasure, one should learn at the same time.” Indeed, almost all instructors will learn something new from the book (e.g. the potential-theoretic proof of Skorokhod embedding) and at the same time, it is attractive and approachable for students. —Yuval Peres, Microsoft With many examples in each section that enhance the presentation, this book is a welcome addition to the collection of books that serve the needs of advanced undergraduate as well as first year graduate students. The pace is leisurely which makes it more attractive as a text. —Srinivasa Varadhan, Courant Institute, New York This book covers in a leisurely manner all the standard material that one would want in a full year probability course with a slant towards applications in financial analysis at the graduate or senior undergraduate honors level. It contains a fair amount of measure theory and real analysis built in but it introduces sigma-fields, measure theory, and expectation in an especially elementary and intuitive way. A large variety of examples and exercises in each chapter enrich the presentation in the text.

Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.

A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.

This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.