In this deftly reasoned book, a columnist for The Financial Times and Slate argues that, despite the everyday insanity, life is logical after all, and he explores the surprisingly rational choices that shape the world.

    KEY TOPICS: This classic book enables readers to make connections between classical and modern physics - an indispensable part of a physicist's education. In this new edition, Beams Medal winner Charles Poole and John Safko have updated the book to include the latest topics, applications, and notation, to reflect today's physics curriculum. They introduce readers to the increasingly important role that nonlinearities play in contemporary applications of classical mechanics. New numerical exercises help readers to develop skills in how to use computer techniques to solve problems in physics. Mathematical techniques are presented in detail so that the book remains fully accessible to readers who have not had an intermediate course in classical mechanics. MARKET: For college instructors and students.

    But Steven E. Landsburg...is one economist who fits the bill. In a wide-ranging, easily digested, unbelievably contrarian survey of everything from why popcorn at movie houses costs so much to why recycling may actually reduce the number of trees on the planet, the University of Rochester professor valiantly turns the discussion of vexing economic questions into an activity that ordinary people might enjoy. -- Joe Queenan, The Wall Street Journal The Armchair Economist is a wonderful little book, written by someone for whom English is a first (and beloved) language, and it contains not a single graph or equation...Landsburg presents fascinating concepts in a form easily accessible to noneconomists. -- Erik M. Jensen, The Cleveland Plain Dealer ...enormous fun from its opening page...Landsburg has done something extraordinary: He has expounded basic economic principles with wit and verve. -- Dan Seligman, Fortune

    Like its predecessors, the seventh edition includes the absolute minimum of mathematical/statistical notation necessary to teach the material. Concepts are fully explained in simple, easy-to-understand language as they are presented, making the book an excellent source from which to learn and teach. After each discussion, readers are guided through real-world examples to show how book principles work in professional practice. Includes easy-to-understand explanations of difficult statistical topics, such as sampling distributions, relationship between confidence level and confidence interval, interpreting r-square. A complete package of teaching/learning aids is provided in every chapter, including chapter review exercises, chapter concepts tests,"Statistics at Work" conceptual cases, "Computer Database Exercises," "From the Textbook to the Real-World Examples." This ISBN is in two volumes Part A and Part B.

    How did this marvel of self-organized complexity evolve? How is wealth created within this system? And how can wealth be increased for the benefit of individuals, businesses, and society? In The Origin of Wealth, Eric D. Beinhocker argues that modern science provides a radical perspective on these age-old questions, with far-reaching implications. According to Beinhocker, wealth creation is the product of a simple but profoundly powerful evolutionary formula: differentiate, select, and amplify. In this view, the economy is a "complex adaptive system" in which physical technologies, social technologies, and business designs continuously interact to create novel products, new ideas, and increasing wealth. Taking readers on an entertaining journey through economic history, from the Stone Age to modern economy, Beinhocker explores how "complexity economics" provides provocative insights on issues ranging from creating adaptive organizations to the evolutionary workings of stock markets to new perspectives on government policies. A landmark book that shatters conventional economic theory, The Origin of Wealth will rewire our thinking about how we came to be here—and where we are going.

    From central banks to brokerages to multinationals, institutional investors are flocking to a new generation of exotic and complex options contracts and derivatives. But the promise of ever larger profits also creates the potential for catastrophic trading losses. Now more than ever, the key to trading derivatives lies in implementing preventive risk management techniques that plan for and avoid these appalling downturns. Unlike other books that offer risk management for corporate treasurers, Dynamic Hedging targets the real-world needs of professional traders and money managers. Written by a leading options trader and derivatives risk advisor to global banks and exchanges, this book provides a practical, real-world methodology for monitoring and managing all the risks associated with portfolio management. Nassim Nicholas Taleb is the founder of Empirica Capital LLC, a hedge fund operator, and a fellow at the Courant Institute of Mathematical Sciences of New York University. He has held a variety of senior derivative trading positions in New York and London and worked as an independent floor trader in Chicago. Dr. Taleb was inducted in February 2001 in the Derivatives Strategy Hall of Fame. He received an MBA from the Wharton School and a Ph.D. from University Paris-Dauphine.

    Anchored by six megabanks—Bank of America, JPMorgan Chase, Citigroup, Wells Fargo, Goldman Sachs, and Morgan Stanley—which together control assets amounting, astonishingly, to more than 60 percent of the country’s gross domestic product, these financial institutions (now more emphatically “too big to fail”) continue to hold the global economy hostage, threatening yet another financial meltdown with their excessive risk-taking and toxic “business as usual” practices. How did this come to be—and what is to be done? These are the central concerns of 13 Bankers, a brilliant, historically informed account of our troubled political economy. In 13 Bankers, Simon Johnson—one of the most prominent and frequently cited economists in America (former chief economist of the International Monetary Fund, Professor of Entrepreneurship at MIT, and author of the controversial “The Quiet Coup” in The Atlantic)—and James Kwak give a wide-ranging, meticulous, and bracing account of recent U.S. financial history within the context of previous showdowns between American democracy and Big Finance: from Thomas Jefferson to Andrew Jackson, from Theodore Roosevelt to Franklin Delano Roosevelt. They convincingly show why our future is imperiled by the ideology of finance (finance is good, unregulated finance is better, unfettered finance run amok is best) and by Wall Street’s political control of government policy pertaining to it. As the authors insist, the choice that America faces is stark: whether Washington will accede to the vested interests of an unbridled financial sector that runs up profits in good years and dumps its losses on taxpayers in lean years, or reform through stringent regulation the banking system as first and foremost an engine of economic growth. To restore health and balance to our economy, Johnson and Kwak make a radical yet feasible and focused proposal: reconfigure the megabanks to be “small enough to fail.” Lucid, authoritative, crucial for its timeliness, 13 Bankers is certain to be one of the most discussed and debated books of 2010.

    The new edition continues to reflect the conversational style and clarity that has made this a leader in the market. It explores the key concepts and principles while using the PepsiCo financial statement to clearly show how the information is applied in the real world. The book has also been updated with the latest data as to reflect today's business environment.

    Non- mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms. Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance-all of which are problems that occur frequently in practice. The text illustrates all parts of the modeling process through many hands-on, real-life examples. And every chapter contains extensive R code f

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    But building a machine learning system requires that you make practical decisions: Should you collect more training data? Should you use end-to-end deep learning? How do you deal with your training set not matching your test set? and many more. Historically, the only way to learn how to make these "strategy" decisions has been a multi-year apprenticeship in a graduate program or company. This is a book to help you quickly gain this skill, so that you can become better at building AI systems.

    While market forces play a role in this stark picture, politics has shaped those market forces. In this best-selling book, Nobel Prize–winning economist Joseph E. Stiglitz exposes the efforts of well-heeled interests to compound their wealth in ways that have stifled true, dynamic capitalism. Along the way he examines the effect of inequality on our economy, our democracy, and our system of justice. Stiglitz explains how inequality affects and is affected by every aspect of national policy, and with characteristic insight he offers a vision for a more just and prosperous future, supported by a concrete program to achieve that vision.

    

    R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you'll need to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You'll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you're done, you won't just know how to write R programs, you'll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES - Exploring R, RStudio, and R packages - Using R for math: variable types, vectors, calling functions, and more - Exploiting data structures, including data.frames, matrices, and lists - Creating attractive, intuitive statistical graphics - Writing user-defined functions - Controlling program flow with if, ifelse, and complex checks - Improving program efficiency with group manipulations - Combining and reshaping multiple datasets - Manipulating strings using R's facilities and regular expressions - Creating normal, binomial, and Poisson probability distributions - Programming basic statistics: mean, standard deviation, and t-tests - Building linear, generalized linear, and nonlinear models - Assessing the quality of models and variable selection - Preventing overfitting, using the Elastic Net and Bayesian methods - Analyzing univariate and multivariate time series data - Grouping data via K-means and hierarchical clustering - Preparing reports, slideshows, and web pages with knitr - Building reusable R packages with devtools and Rcpp - Getting involved with the R global community

    This work offers accesible coverage of the fundamentals of electrodynamics, enhanced with with discussion points, examples and exercises.