Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    World History

    Drawing heavily on the author's own real-world experiences, the book stresses design and analysis. Coverage is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. The second is a reference section, which includes a catalog of the 75 most important algorithmic problems. By browsing this catalog, readers can quickly identify what the problem they have encountered is called, what is known about it, and how they should proceed if they need to solve it. This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference. This work can also readily be used in an upper-division course or as a student reference guide. THE ALGORITHM DESIGN MANUAL comes with a CD-ROM that contains: * a complete hypertext version of the full printed book. * the source code and URLs for all cited implementations. * over 30 hours of audio lectures on the design and analysis of algorithms are provided, all keyed to on-line lecture notes.

    No graduate student of quantum theory should leave it unread"--W.C Schieve, University of Texas

    Bayesian statistics is taught in most first-year statistics classes across the nation, but there is one major problem that many students (and others who are interested in the theorem) face. The theorem is not intuitive for most people, and understanding how it works can be a challenge, especially because it is often taught without visual aids. In this guide, we unpack the various components of the theorem and provide a basic overview of how it works - and with illustrations to help. Three scenarios - the flu, breathalyzer tests, and peacekeeping - are used throughout the booklet to teach how problems involving Bayes Theorem can be approached and solved. Over 60 hand-drawn visuals are included throughout to help you work through each problem as you learn by example. The illustrations are simple, hand-drawn, and in black and white. For those interested, we have also included sections typically not found in other beginner guides to Bayes Rule. These include: A short tutorial on how to understand problem scenarios and find P(B), P(A), and P(B|A). For many people, knowing how to approach scenarios and break them apart can be daunting. In this booklet, we provide a quick step-by-step reference on how to confidently understand scenarios.A few examples of how to think like a Bayesian in everyday life. Bayes Rule might seem somewhat abstract, but it can be applied to many areas of life and help you make better decisions. It is a great tool that can help you with critical thinking, problem-solving, and dealing with the gray areas of life. A concise history of Bayes Rule. Bayes Theorem has a fascinating 200+ year history, and we have summed it up for you in this booklet. From its discovery in the 1700’s to its being used to break the German’s Enigma Code during World War 2, its tale is quite phenomenal.Fascinating real-life stories on how Bayes formula is used in everyday life.From search and rescue to spam filtering and driverless cars, Bayes is used in many areas of modern day life. We have summed up 3 examples for you and provided an example of how Bayes could be used.An expanded definitions, notations, and proof section.We have included an expanded definitions and notations sections at the end of the booklet. In this section we define core terms more concretely, and also cover additional terms you might be confused about. A recommended readings section.From The Theory That Would Not Die to a few other books, there are a number of recommendations we have for further reading. Take a look! If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you. Bayesian statistics is an incredibly fascinating topic and likely touches your life every single day. It is a very important tool that is used in data analysis throughout a wide-range of industries - so take an easy dive into the theorem for yourself with a visual approach!If you are looking for a short beginners guide packed with visual examples, this booklet is for you.

    Dumb crooks, celebrities gone bad, unsolved mysteries, odd laws, and more—Strange Crime has plenty of stories that will make you ask yourself, “What could they possibly have been thinking?” This easily portable paperback book is ideal for readers on the go. Take it to school, to work, to jury duty!

    How does professional baseball evaluate hitters? Is a singles hitter like Wade Boggs more valuable than a power hitter like David Ortiz? Should NFL teams pass or run more often on first downs? Could professional basketball have used statistics to expose the crooked referee Tim Donaghy? Does money buy performance in professional sports?In Mathletics, Wayne Winston describes the mathematical methods that top coaches and managers use to evaluate players and improve team performance, and gives math enthusiasts the practical tools they need to enhance their understanding and enjoyment of their favorite sports--and maybe even gain the outside edge to winning bets. Mathletics blends fun math problems with sports stories of actual games, teams, and players, along with personal anecdotes from Winston's work as a sports consultant. Winston uses easy-to-read tables and illustrations to illuminate the techniques and ideas he presents, and all the necessary math concepts--such as arithmetic, basic statistics and probability, and Monte Carlo simulations--are fully explained in the examples.After reading Mathletics, you will understand why baseball teams should almost never bunt, why football overtime systems are unfair, why points, rebounds, and assists aren't enough to determine who's the NBA's best player--and much, much more.

    The book is non-theoretical, explaining concepts intuitively and teaching problem solving through worked examples and step-by-step instructions. This edition places more emphasis on conceptual understanding and understanding results. This edition also features increased emphasis on Excel, MINITAB, and the TI-83 Plus and TI 84-Plus graphing calculators, computing technologies commonly used in such courses.

    History is designed to meet the scope and sequence requirements of most introductory courses. The text provides a balanced approach to U.S. history, considering the people, events, and ideas that have shaped the United States from both the top down (politics, economics, diplomacy) and bottom up (eyewitness accounts, lived experience). U.S. History covers key forces that form the American experience, with particular attention to issues of race, class, and gender.

    Indispensable reference for graduates and undergraduates.

    The first chapter describes basic features of the program and shows how to use it in simple arithmetic operations with scalars. The next two chapters focus on the topic of arrays (the basis of MATLAB), while the remaining text covers a wide range of other applications. Computer screens, tutorials, samples, and homework questions in math, science, and engineering, provide the student with the practical hands-on experience needed for total proficiency.

    The author defines all terms, points out potential pitfalls in algebraic calculation, and makes problem solving a fun activity. New in this edition are painless approaches to understanding and graphing linear equations, solving systems of linear inequalities, and graphing quadratic equations. Barron’s popular Painless Series of study guides for middle school and high school students offer a lighthearted, often humorous approach to their subjects, transforming details that might once have seemed boring or difficult into a series of interesting and mentally challenging ideas. Most titles in the series feature many fun-to-solve “Brain Tickler” problems with answers at the end of each chapter.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.