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Naked Statistics: Stripping the Dread from the Data 1st Edition

4.4 out of 5 stars 346 customer reviews
ISBN-13: 978-0393347777
ISBN-10: 039334777X
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Editorial Reviews

Review

“While a great measure of the book’s appeal comes from Mr. Wheelan’s fluent style―a natural comedian, he is truly the Dave Barry of the coin toss set―the rest comes from his multiple real world examples illustrating exactly why even the most reluctant mathophobe is well advised to achieve a personal understanding of the statistical underpinnings of life.” (New York Times)

“The best math teacher you never had. [Naked Statistics] is filled with practical lessons, like how to judge the validity of polls, why you should never buy a lottery ticket, and how to keep an eye out for red flags in public statements.” (San Francisco Chronicle)

Naked Statistics is an apt title. Charles Wheelan strips away the superfluous outer garments and exposes the underlying beauty of the subject in a way that everyone can appreciate.” (Hal Varian, chief economist at Google)

“I cannot stress enough the importance of Americans’ need to understand statistics―the basis for a great deal of what we hear and read these days―and I cannot stress enough the value of Wheelan’s book in giving readers an approachable avenue to understanding statistics. Almost anyone interested in sports, politics, business, and the myriad of other areas in which statistics rule the roost today will benefit from this highly readable, on-target, and important book.” (Frank Newport, Gallup editor-in-chief)

“A fun, engaging book that shows why statistics is a vital tool for anyone who wants to understand the modern world.” (Jacob J. Goldstein, "Planet Money" on NPR)

“Two phrases you don’t often see together: ‘statistics primer’ and ‘rollicking good time.’ Until Charlie Wheelan got to it, that is. This book explains the way statistical ideas can help you understand much of everyday life.” (Austan Goolsbee, professor of economics at the University of Chicago and former chairman of the Council of Economic Advisers)

About the Author

Charles Wheelan is the author of the best-selling Naked Statistics and Naked Economics and is a former correspondent for The Economist. He teaches public policy and economics at Dartmouth College and lives in Hanover, New Hampshire, with his family.
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Product Details

  • Paperback: 304 pages
  • Publisher: W. W. Norton & Company; 1 edition (January 13, 2014)
  • Language: English
  • ISBN-10: 039334777X
  • ISBN-13: 978-0393347777
  • Product Dimensions: 5.5 x 0.8 x 8.3 inches
  • Shipping Weight: 10.4 ounces (View shipping rates and policies)
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (346 customer reviews)
  • Amazon Best Sellers Rank: #2,504 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Hardcover Verified Purchase
Yes, there are lots of "dear reader" type comments throughout the book. Yes, the examples and references are drawn from up-to-the-minute pop culture. And, yes, if you don't know very much about statistics and probability you can learn fairly "painlessly" in this book.

One drawback: you really, really need to read the entire book from start to finish to really understand all of the concepts. This is not a reference book in which you can "jump around" or just go to the parts you have questions about.

It's like being given a prescription for antibiotics; you really need to read every chapter in the book, to "take it all." Concepts build on previous chapters, up to the final chapter. Don't stop or you will miss out!

On the other hand, this is not a book for someone who wants to quickly, at-a-glance understand probability or who wants to get a solid definition of any statistical concept, such as confidence level or regression analysis. It is not specifically a reference book.

I confess, my prejudice is for more concise information without all the "fluff." On the other hand, I work with opinion survey statistics almost every day of my worklife, so I don't need to be lured in with tales of baseball (in which I have no interest) or discussions of what's behind the doors in Let's Make a Deal. (In fact, I have never, ever seen that show.)

However, if you are in business or education or health care and don't have a complete grasp of statistics, I recommend you read this book. If you want to better understand whether you should buy a lottery ticket or buy insurance and you don't understand probability theory, I recommend this book to you.
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Format: Hardcover
This book will not teach you the mathematics behind statistics. This book is about making you understand what you are doing when you are doing statistics. Thus it is a great complement to a university course where you might learn how to plug in numbers in SPSS or MATLAB and get a p-value but don't really understand the assumptions involved and the potential pitfalls that must be considered.
Though I have studied some statistics at university level this book still provided a fresh valuable perspective on many statistical issues. It also gives examples of many, often costly mistakes scientists made in the past using statistics.

The analogy I used in the title (taken from this book), really captures an important aspect of statistics. If used properly statistics can tell us if a medication, or a certain policy is effective. If used improperly, it can lead to erroneous medical advice with fatal consequences, in the literal sense.

I would recommend this book if you are taking statistics but often don't know what you are really doing or how what you are doing relates to real life issues. Alternatively, this book can also be read by people who don't know any statistics but want to understand what it is all about without having to learn to do the actual math. If you are already an advanced student in statistics and know what you are doing (and know what not to do), then this book might not be for you.
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Format: Hardcover
It was worth the price of the book for this alone. All these years I have read and listened to various explanations of the Monty Hall problem, in which a contestant is given the choice of what is behind one of three doors. Behind two doors there are goats, behind one door there's a new car. The contestant chooses Door #1 and Monty Hall, the host of the game show, opens Door #2, revealing a goat. Then he asks the contestant if she wants to change her choice. The intuitive answer is that it makes no difference, but the correct answer is that she should switch. I could never understand why, but author Charles Wheelan has finally convinced me once and for all.

The rest of the book is also good, although I could do without the many sports examples, which were not enlightening since they required knowing (and caring) more about sports than I do. (What is a passer rating, anyway?)

Wheelan explains concepts clearly and tells why statistics and probability matter. So even, if like Wheelan, you never warmed to calculus, you can still exercise your math muscles and decide for yourself whether the latest poll or alarming statistic is credible or just another goat behind the door.
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Format: Hardcover
Statistics are everywhere; the author's intent is to make them interesting while simplifying the topic. He begins by explaining the mean, how the median is less influenced by outliers, standard deviation (spread), how the weighting of index components affects results, correlation vs. causation, inflation-adjustment, specificity vs. accuracy, the importanace of using the appropriate unit of analysis (eg. people, instead of nations when analyzing the benefits of globalization), statistical vs. operational significance, and how performance data is sometimes manipulated (eg. reclassifying dropouts as something else, holding back students, not operating on the most seriously ill to reduce death rates).

One of the most interesting segments was that explaining the reasoning and high certainty of looking good on blind taste tests using those who previously preferred a competitor's offering (eg. Coke vs. Pepsi, some beers) when there's little discernible difference between the two products. Another was his simple explanation of how random occurrences such as coin flips can make one look superior at the end of a series of selecting those getting heads - when there obviously was no difference; similarly often in eg. mutual fund performance, etc. Still another - pointing out the erroneous possibilities of claiming a DNA match when done on 9 loci (a common method) - supposedly only 1 in 113 billion, vs. the reality of thousands within a single database.

Expected values are another important topic addressed - eg. point-after-touchdown expected results vs. two-point conversions; never buy a lottery ticket or expect to come out ahead (on average) buying product insurance.

Testing for disease doesn't always make sense.
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