Why do we mistrust people more in the UK than in Japan? Why do Americans have higher rates of teenage pregnancy than the French? What makes the Swedish thinner than the Greeks? The answer: inequality. This groundbreaking book, based on years of research, provides hard evidence to show how almost everything—-from life expectancy to depression levels, violence to illiteracy-—is affected not by how wealthy a society is, but how equal it is. Urgent, provocative and genuinely uplifting, The Spirit Level has been heralded as providing a new way of thinking about ourselves and our communities, and could change the way you see the world.

    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.

    "Using Econometrics: A Practical Guide "provides readers with a practical introduction that combines single-equation linear regression analysis with real-world examples and exercises. This text also avoids complex matrix algebra and calculus, making it an ideal text for beginners. New problem sets and added support make "Using Econometrics" modern and easier to use.

    Information is provided on the fundamental concepts of table and graph design, the numbers and knowledge most suitable for display in a graphic form, the best tabular means to communicate certain ideas, and the component-level aspects of design. Analysts, technicians, and managers will appreciate the solid theory behind this outline for ensuring that tables and graphs present quantitative business information in a truthful, attractive format that facilitates better decision making.

    It is designed as a reference for students in the physical sciences and engineering.

    With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    

    If you’ve ever sought a job or hired someone, applied to college or guided your child into a good kindergarten, asked someone out on a date or been asked out, you’ve participated in a kind of market. Most of the study of economics deals with commodity markets, where the price of a good connects sellers and buyers. But what about other kinds of “goods,” like a spot in the Yale freshman class or a position at Google? This is the territory of matching markets, where “sellers” and “buyers” must choose each other, and price isn’t the only factor determining who gets what.Alvin E. Roth is one of the world’s leading experts on matching markets. He has even designed several of them, including the exchange that places medical students in residencies and the system that increases the number of kidney transplants by better matching donors to patients. In Who Gets What — And Why, Roth reveals the matching markets hidden around us and shows how to recognize a good match and make smarter, more confident decisions.

    Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    The economic narratives that underpinned these eras—the gold standard, the Bretton Woods regime, the "Washington Consensus"—brought great success and great failure. In this eloquent challenge to the reigning wisdom on globalization, Dani Rodrik offers a new narrative, one that embraces an ineluctable tension: we cannot simultaneously pursue democracy, national self-determination, and economic globalization. When the social arrangements of democracies inevitably clash with the international demands of globalization, national priorities should take precedence. Combining history with insight, humor with good-natured critique, Rodrik's case for a customizable globalization supported by a light frame of international rules shows the way to a balanced prosperity as we confront today's global challenges in trade, finance, and labor markets.

    Since then, that share has plummeted to where it was in 1900. As Richard Baldwin explains, this reversal of fortune reflects a new age of globalisation that is drastically different from the old.In the 1800s, globalisation leaped forward when steam power and international peace lowered the costs of moving goods across borders. This triggered a self-fueling cycle of industrial agglomeration and growth that propelled today's rich nations to dominance. That was the Great Divergence. The new globalisation is driven by information technology, which has radically reduced the cost of moving ideas across borders. This has made it practical for multinational firms to move labor-intensive work to developing nations. But to keep the whole manufacturing process in sync, the firms also shipped their marketing, managerial, and technical know-how abroad along with the offshored jobs. The new possibility of combining high tech with low wages propelled the rapid industrialisation of a handful of developing nations, the simultaneous deindustrialisation of developed nations, and a commodity supercycle that is only now petering out. The result is today's Great Convergence.Because globalisation is now driven by fast-paced technological change and the fragmentation of production, its impact is more sudden, more selective, more unpredictable, and more uncontrollable. As The Great Convergence shows, the new globalisation presents rich and developing nations alike with unprecedented policy challenges in their efforts to maintain reliable growth and social cohesion.

    In the years that followed, as Wall Street boomed and financial wheeler-dealers made vast profits, the international crises of the 1990s faded from memory. But now depression economics has come to America: when the great housing bubble of the mid-2000s burst, the U.S. financial system proved as vulnerable as those of developing countries caught up in earlier crises and a replay of the 1930s seems all too possible. In this new, greatly updated edition of The Return of Depression Economics, Krugman shows how the failure of regulation to keep pace with an increasingly out-of-control financial system set the United States, and the world as a whole, up for the greatest financial crisis since the 1930s. He also lays out the steps that must be taken to contain the crisis, and turn around a world economy sliding into a deep recession. Brilliantly crafted in Krugman's trademark style--lucid, lively, and supremely informed--this new edition of The Return of Depression Economics will become an instant cornerstone of the debate over how to respond to the crisis.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    While the mathematics is there, the effort is not all concentrated on proofs. Strang's emphasis is on understanding. He explains concepts, rather than deduces. This book is written in an informal and personal style and teaches real mathematics. The gears change in Chapter 2 as students reach the introduction of vector spaces. Throughout the book, the theory is motivated and reinforced by genuine applications, allowing pure mathematicians to teach applied mathematics.

    Whether you're building the next killer app, investing in a startup, or simply curious about the technology, this practical book is essential reading.Bitcoin, the first successful decentralized digital currency, is still in its infancy and it's already spawned a multi-billion dollar global economy. This economy is open to anyone with the knowledge and passion to participate. Mastering Bitcoin provides you with the knowledge you need (passion not included).This book includes:A broad introduction to bitcoin--ideal for non-technical users, investors, and business executivesAn explanation of the technical foundations of bitcoin and cryptographic currencies for developers, engineers, and software and systems architectsDetails of the bitcoin decentralized network, peer-to-peer architecture, transaction lifecycle, and security principlesOffshoots of the bitcoin and blockchain inventions, including alternative chains, currencies, and applicationsUser stories, analogies, examples, and code snippets illustrating key technical concepts