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.
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.
Part I, The Theory of Probability, starts with elementary set theory and proceeds through basic measure and probability, random variables, integration and mathematical expectation. It concludes with an extensive survey of models for distributions of random variables. Part II, The Theory of Statistics, begins with sampling theory and distribution theory for statistics from normal populations, proceeds to asymptotic (large-sample) theory, and on to point and interval estimation and tests of parametric hypotheses. The last three chapters cover tests of nonparametric hypotheses, Bayesian methods, and linear and nonlinear regression.
Researchers and graduate students in applied fields such as actuarial science, biostatistics, economics, finance, mathematical psychology, and systems engineering will find this book to be a valuable learning tool and an essential reference.
Chapter 1: Probability on Abstract Sets (476 KB)
Chapter 5: Sampling Distributions (405 KB)
Request Inspection Copy
Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates