The Fourth Edition builds on this strength with new examples, additional applications and increased cryptology coverage. Up-to-date information on the latest discoveries is included.Elementary Number Theory and Its Applications provides a diverse group of exercises, including basic exercises designed to help students develop skills, challenging exercises and computer projects. In addition to years of use and professor feedback, the fourth edition of this text has been thoroughly accuracy checked to ensure the quality of the mathematical content and the exercises.

    Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    Written not from a post-crisis perspective – but from a preventative point of view – this book traces the development of financial derivatives from bonds to credit default swaps, and shows how mathematical formulas went beyond pricing to expand their use to the point where they dwarfed the real economy. You'll learn how the deadly allure of their ice-cold beauty has misled generations of economists and investors, and how continued reliance on these formulas can either assist future economic development, or send the global economy into the financial equivalent of a cardiac arrest. Rather than rehash tales of post-crisis fallout, this book focuses on preventing the next one. By exploring the heart of the shadow economy, you'll be better prepared to ride the rough waves of finance into the turbulent future. Delve into one of the world's least-understood but highest-impact industries Understand the key principles of quantitative finance and the evolution of the field Learn what quantitative finance has become, and how it affects us all Discover how the industry's next steps dictate the economy's future How do you create a quadrillion dollars out of nothing, blow it away and leave a hole so large that even years of "quantitative easing" can't fill it – and then go back to doing the same thing? Even amidst global recovery, the financial system still has the potential to seize up at any moment. The Money Formula explores the how and why of financial disaster, what must happen to prevent the next one.

    There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study.Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.)Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

    It has also often required oppressive and incomprehensible mathematics. Game Theory at Work steers around math and pedagogy to make this innovative tool accessible to a larger audience and allow all levels of business to use it to both improve decision-making skills and eliminate potentially lethal uncertainty.This proven tool requires everyone in an organization to look at the competition, guage his or her own responses to their actions, and then establish an appropriate strategy. Game Theory at Work will help business leaders at all levels improve their overall performance in:NegotiatingDecision makingEstablishing strategic alliancesMarketingPositioningBrandingPricing

    The strengths of these texts are characterized by mathematical integrity, comprehensive discussions of the concepts of calculus, and an impressively large collection of worked examples and illustrative figures.

    That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us.” If we can toss aside our fears and learn to approach them clearly—understanding how our own preconceptions lead us astray—statistics can point to ways we can live better and work smarter.As “perhaps the best popular economics writer in the world” (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.

    In addition to fine-tuning and streamlining the prose and the overall presentation, the authors have comprehensively updated the text and the applications to reflect recent economic developments and topics of current interest. Students in particular will find the Study Guide, with its practice questions, exercises, and problems, to be an excellent source of study support and extra review material. It is available in both a one- and a two-volume edition.

    Daft addresses themes and issues directly relevant to both the everyday demands and significant challenges facing businesses today. Comprehensive coverage helps develop managers able to look beyond traditional techniques and ideas to tap into a full breadth of management skills. With the best in proven management and new competencies that harness creativity, D.A.F.T. is Management.

    Sufficient information about General Phonetics has been included in the book, with a view to facilitating the reader's understanding of the Phonetics of English. Plenty of examples are given from English, Tamil, Hindi and Urdu/Arabic to illustrate the points made. There are a number of diagrams throughout the book,illustrating the articulation of the sounds of English. The book also includes some information about General Phonology and the Phonology of English. A few sentences, dialogues and a popular tale have been given at the end of the book, both in orthography and in simple phonemic transcription. The book covers the Phonetics/Phonology syllabus of most Indian universities and ELT institutes

    Emphasis on developing algebraic skills is extended to the exercises--including both drill problems and applications. The authors work through examples and explanations with a blend of rigor and accessibility. In addition, they have refined the flow, transitions, organization, and portioning of the content over many editions to optimize learning for readers. The table of contents covers a wide range of topics efficiently, enabling readers to gain a diverse understanding.

    This text uses a unified approach based on a single economics model that provides readers with a clear understanding of macroeconomics and its classical and Keynesian assumptions. Introduction: Introduction to Macroeconomics; The Measurement and Structure of the National Economy. Long-Run Economic Performance: Productivity, Output, and Employment; Consumption, Saving, and Investment; Saving and Investment in the Open Economy; Long-Run Economic Growth; The Asset Market, Money, and Prices. Business Cycles and Macroeconomic Policy: Business Cycles; The IS-LM/AD-AS Model: A General Framework for Macroeconomic Analysis; Classical Business Cycle Analysis: Market-Clearing Macroeconomics; Keynesianism: The Macroeconomics of Wage and Price Rigidity. Macroeconomic Policy: Its Environment and Institutions: Unemployment and Inflation; Exchange Rates, Business Cycles, and Macroeconomic Policy in the Open Economy; Monetary Policy and the Federal Reserve System; Government Spending and Its Financing. For all readers interested in intermediate macroeconomics.

    Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.

    

    Dozens of examples in innumeracy show us how it affects not only personal economics and travel plans, but explains mis-chosen mates, inappropriate drug-testing, and the allure of pseudo-science.