In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer?How Not to Be Wrong presents the surprising revelations behind all of these questions and many more, using the mathematician’s method of analyzing life and exposing the hard-won insights of the academic community to the layman—minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God.Ellenberg pulls from history as well as from the latest theoretical developments to provide those not trained in math with the knowledge they need. Math, as Ellenberg says, is “an atomic-powered prosthesis that you attach to your common sense, vastly multiplying its reach and strength.” With the tools of mathematics in hand, you can understand the world in a deeper, more meaningful way. How Not to Be Wrong will show you how.

    He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of FiveThirtyEight.com. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the "prediction paradox": The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good-or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary-and dangerous-science.Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.

    But what if free will doesn't exist? What if our lives are largely predetermined, hardwired in our brains - and our choices over what we eat, who we fall in love with, even what we believe are not real choices at all? Neuroscience is challenging everything we think we know about ourselves, revealing how we make decisions and form our own reality, unaware of the role of our unconscious minds. Did you know, for example, that:* You can carry anxieties and phobias across generations of your family?* Your genes and pleasure and reward receptors in your brain will determine how much you eat?* We can sniff out ideal partners with genes that give our offspring the best chance of survival?Leading neuroscientist Hannah Critchlow draws vividly from everyday life and other experts in their field to show the extraordinary potential, as well as dangers, which come with being able to predict our likely futures - and looking at how we can alter what's in store for us. Lucid, illuminating, awe-inspiring The Science of Fate revolutionises our understanding of who we are - and empowers us to help shape a better future for ourselves and the wider world.

    Wouldn't it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships.Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator Contains numerous examples and descriptions of patterns and outliers and explains how to show them Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.

    The analytic material is accompanied by many applications, examples, and exercises. The theory of noncooperative games studies the behavior of agents in any situation where each agent's optimal choice may depend on a forecast of the opponents' choices. "Noncooperative" refers to choices that are based on the participant's perceived selfinterest. Although game theory has been applied to many fields, Fudenberg and Tirole focus on the kinds of game theory that have been most useful in the study of economic problems. They also include some applications to political science. The fourteen chapters are grouped in parts that cover static games of complete information, dynamic games of complete information, static games of incomplete information, dynamic games of incomplete information, and advanced topics.--mitpress.mit.edu

    Volume 2: From the Great Qing Empire through the People's Republic of China (1644—2009).

    This second edition is appropriate as a supplementary (companion) text for any college-level course covering digital signal processing.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

    According to the authors,effective human resource management is necessary for a firm to gain true competitive advantage. The three challenges companies face are the global challenge,the challenge of meeting stakeholder needs,and the high performance work practices challenge. HUMAN RESOURCE MANAGEMENT provides students with the technical background needed to be a successful HR professional,to manage HR effectively,and most importantly to be a knowledgeable consumer of HR products and services. The text also emphasizes how managers can more effectively acquire,develop,compensate,and manage the internal and external environment that relates to the management of human resources.

    Each chapter contains integrated worked examples and chapter tests. This edition has the ancillary ATLAST computer exercise guide and new MATLAB and Maple guides.

    In Confessions of a Subprime Lender: An Insider's Tale of Greed, Fraud, and Ignorance, he reveals the truth about how the subprime lending business spiraled out of control, pushed home prices to unsustainable levels, and turned unqualified applicants into qualified borrowers through creative financing. Learn about the ways the mortgage industry can be fixed with his twenty suggestions for critical change.

    Sullivan Elin M. Wicks C. Patrick Koelling   A succinct job description for an engineer consists of just two words: problem solver. Broadly speaking, engineers use knowledge to find new ways of doing things economically. Engineering design solutions do not exist in a vacuum, but within the context of a business opportunity. Truly, every problem has multiple solutions, so the question is, “How does one rationally select the design solution with the most favorable economic result?” The answer to this question can also be put forth in two words: engineering economy. This field of engineering provides a systematic framework for evaluating the economic aspects of competing design solutions. Just as engineers model the stress on a support column or the thermodynamic properties of a steam turbine, they must also model the economic impact of their engineering recommendations. Engineering economy is the subject of this textbook.   Highlights of Engineering Economy, Fourteenth Edition: ×           Fifty percent of end-of-chapter problems are new or revised. ×           A bank of algorithmically generated test questions is available to adopting instructors. ×           Fundamentals of Engineering (FE) exam-style questions are included among the end-of-chapter problem sets. ×           Spreadsheet models are integratedthroughout. ×           An appendix on the basics of accounting is included in Chapter 2. ×           Chapter 3 on Cost Estimation appears early in the book. ×           An appendix on techniques for using Excel in engineering economy is available for reference. ×           Numerous comprehensive examples and case studies appear throughout the book. ×           Extended learning exercises appear in most chapters. ×           Personal finance problems are featured in most chapters. ×           Many pointers to relevant Web sites are provided.   ISBN-13: 978-0-13-614297-3 ISBN-10: 0-13-614297-4

    Professor Resnick presents a fundamental and unified development of the subject with unusually clear discussions of the aspects that usually trouble beginners. He includes, for example, a section on the common sense of relativity. His presentation is lively and interspersed with historical, philosophical and special topics (such as the twin paradox) that will arouse and hold the reader's interest. You'll find many unique features that help you grasp the material, such as worked-out examples, summary tables, thought questions and a wealth of excellent problems. The emphasis throughout the book is physical. The experimental background, experimental confirmation of predictions, and the physical interpretation of principles are stressed. The book treats relativistic kinematics, relativistic dynamics, and relativity and electromagnetism and contains special appendices on the geometric representation of space-time and on general relativity. Its organization permits an instructor to vary the length and depth of his treatment and to use the book either with or following classical physics. These features make it an ideal companion for introductory course

    It provides reality-based practical advice about how to actually conduct policy analysis and demonstrates the application of advanced analytic techniques.

    This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrated by graphics, formulas, and plenty of solved examples. Before you know it, you'll learn to apply statistical reasoning and statistical techniques, from basic concepts of probability and hypothesis testing to multivariate analysis. Organized into four distinct sections, Statistics in a Nutshell offers you:Introductory material: Different ways to think about statistics Basic concepts of measurement and probability theoryData management for statistical analysis Research design and experimental design How to critique statistics presented by others Basic inferential statistics: Basic concepts of inferential statistics The concept of correlation, when it is and is not an appropriate measure of association Dichotomous and categorical data The distinction between parametric and nonparametric statistics Advanced inferential techniques: The General Linear Model Analysis of Variance (ANOVA) and MANOVA Multiple linear regression Specialized techniques: Business and quality improvement statistics Medical and public health statistics Educational and psychological statistics Unlike many introductory books on the subject, Statistics in a Nutshell doesn't omit important material in an effort to dumb it down. And this book is far more practical than most college texts, which tend to over-emphasize calculation without teaching you when and how to apply different statistical tests. With Statistics in a Nutshell, you learn how to perform most common statistical analyses, and understand statistical techniques presented in research articles. If you need to know how to use a wide range of statistical techniques without getting in over your head, this is the book you want.