A New York Times bestseller "Brilliant, funny…the best math teacher you never had." —San Francisco Chronicle Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called "sexy." From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

In this "important and comprehensive" guide to statistical thinking (New Yorker), discover how data literacy is changing the world and gives you a better understanding of life’s biggest problems. Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: (1) queries about the effects of potential interventions, (also called "causal effects" or "policy evaluation") (2) queries about probabilities of counterfactuals, (including assessment of "regret," "attribution" or "causes of effects") and (3) queries about direct and indirect effects (also known as "mediation"). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both. The tools are demonstrated in the analyses of mediation, causes of effects, and probabilities of causation. -- p. 1.

Seeks to provide an engaging and comprehensive primer to economics that explains key concepts without technical jargon and using common-sense examples.

Charles Wheelan’s wonderfully whimsical, best-selling Naked series tackles the weird, surprisingly colorful world of money and banking. Consider the $20 bill. It has no more value, as a simple slip of paper, than Monopoly money. Yet even children recognize that tearing one into small pieces is an act of inconceivable stupidity. What makes a $20 bill actually worth twenty dollars? In the third volume of his best-selling Naked series, Charles Wheelan uses this seemingly simple question to open the door to the surprisingly colorful world of money and banking. The search for an answer triggers countless other questions along the way: Why does paper money (“fiat currency” if you want to be fancy) even exist? And why do some nations, like Zimbabwe in the 1990s, print so much of it that it becomes more valuable as toilet paper than as currency? How do central banks use the power of money creation to stop financial crises? Why does most of Europe share a common currency, and why has that arrangement caused so much trouble? And will payment apps, bitcoin, or other new technologies render all of this moot? In Naked Money, Wheelan tackles all of the above and more, showing us how our banking and monetary systems should work in ideal situations and revealing the havoc and suffering caused in real situations by inflation, deflation, illiquidity, and other monetary effects. Throughout, Wheelan’s uniquely bright-eyed, whimsical style brings levity and clarity to a subject often devoid of both. With illuminating stories from Argentina, Zimbabwe, North Korea, America, China, and elsewhere around the globe, Wheelan demystifies the curious world behind the paper in our wallets and the digits in our bank accounts.

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.

Here, by popular demand, is the updated edition to Joel Best's classic guide to understanding how numbers can confuse us. In his new afterword, Best uses examples from recent policy debates to reflect on the challenges to improving statistical literacy. Since its publication ten years ago, Damned Lies and Statistics has emerged as the go-to handbook for spotting bad statistics and learning to think critically about these influential numbers.

If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff’s lively and engaging primer clarifies the basic principles of statistics and explains how they’re used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Political backstabbing, rank hypocrisy, and dastardly deception reign in this delightfully entertaining political satire, sure to lift one’s spirits far above the national stage. America is in trouble—at the mercy of a puzzling pathogen. That ordinarily wouldn’t lead to catastrophe, thanks to modern medicine, but there’s just one problem: the government supply of Dormigen, the silver bullet of pharmaceuticals, has been depleted just as demand begins to spike. Set in the near future, The Rationing centers around a White House struggling to quell the crisis—and control the narrative. Working together, just barely, are a savvy but preoccupied president; a Speaker more interested in jockeying for position—and a potential presidential bid—than attending to the minutiae of disease control; a patriotic majority leader unable to differentiate a virus from a bacterium; a strategist with brilliant analytical abilities but abominable people skills; and, improbably, our narrator, a low-level scientist with the National Institutes of Health who happens to be the world’s leading expert in lurking viruses. Little goes according to plan during the three weeks necessary to replenish the stocks of Dormigen. Some Americans will get the life-saving drug and others will not, and nations with their own supply soon offer aid—but for a price. China senses blood and a geopolitical victory, presenting a laundry list of demands that ranges from complete domination of the South China Sea to additional parking spaces at the UN, while India claims it can save the day for the U.S.