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Stat-Spotting: A Field Guide to Identifying Dubious Data 1st Edition

4.7 out of 5 stars 9 customer reviews
ISBN-13: 978-0520257467
ISBN-10: 0520257464
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Editorial Reviews

Review

“An ideal guide for anyone who reads a newspaper, watches television, or surfs the Web. In short, everyone.”
(Joe Swingle Numeracy 2009-07-01)

“Offers an eye-opening field guide to identifying problematic data and concludes by calling for better statistics.”
(Nacada Journal 2012-07-24)

From the Inside Flap

"If you ever scan the newspaper, watch the TV news, or surf the blogs, you should read this charming book. If you're a journalist, read it twice."—James M. Jasper

"As we now swim in information, much of it bogus or biased, spotting dubious data is super important. In Stat-Spotting, Joel Best plays off the format of field guides to give readers good, common sense ways not only to sense bad data but to understand what's wrong. Broken up into short independent sections much like field guides to various flora or fauna, the book is easy and enjoyable to read. Easy, enjoyable, and valuable. I will recommend it to my students, and to others, as a resource for critical consumers of numbers."—Bernard Madison, University of Arkansas

"The purpose of Stat-Spotting is to help readers become more critical consumers of statistical claims. It is an important work addressing a significant problem in contemporary society: thoughtlessness about numerical claims. Best's work here provides a direct, accessible guide to critical readings of statistics."—Neil Lutsky, Carleton College
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Product Details

  • Hardcover: 132 pages
  • Publisher: University of California Press; 1 edition (October 20, 2008)
  • Language: English
  • ISBN-10: 0520257464
  • ISBN-13: 978-0520257467
  • Product Dimensions: 8.3 x 5.5 x 0.9 inches
  • Shipping Weight: 12.8 ounces
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (9 customer reviews)
  • Amazon Best Sellers Rank: #855,267 in Books (See Top 100 in Books)

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Top Customer Reviews

Format: Hardcover
There are many books written on the interpretation of statistical information for the non-specialist. Some are quite engaging and difficult to put down; others are quite boring. I would place this little book roughly in the middle of that range - it's not the most gripping but it is certainly an eye-opener for those seeking guidance in this field. The author, a sociology professor, has divided the book such that each chapter addresses a type of question that a reader should ask when reviewing statistical information that may seem dubious or misleading. Each chapter opens with a brief digression on the issue at hand. This is followed by a practical example, i.e., a statistical "fact" that has been published in some medium and which the author analyzes in order to put this "fact" into perspective and in a manner that the reader can more easily interpret. The writing style is clear, authoritative and accessible to a wide audience. People seeking to make sense of the statistical data that floods our lives every day would benefit greatly from reading this concise little book.
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Statistics are used to support a variety of claims. It takes a trained eye to interpret the validity of a massive amount of statistical data particularly surrounding health care claims. Statistics are not synonymous with facts. Although statistics play a major role in data integrity one must look closer with a dubious eye. Especially since statistics are often used to support a claim or sell a concept. Joel Best takes the most common data marketing tricks and explains them to the lay person in a creative way. The dubious data is laid out before the reader as one would expect to see in an ecology field guide for nature enthusiasts. Therefore, Stat-Spotting fulfills its mission delightfully as promised by presenting a guide for spotting dubious data, "questionable stats". Along with the creative format the author also appeals to the reader's sense of reporting order by covering the "how", the "who" and the "what".
Be on the look out for "fictoids" which the author defines as colorful or erroneous stats used as a hyperbole. Where upon discovery a loud bell should ring in one's head as a reminder to not take literally but instead look deeper. In order to master stat spotting, here are a few simple rules to keep in mind:
1. Having a sense of scale allows you to understand the magnitude and validity of data.
2. The more severe or dramatic the case the more likely it is to be extremely rare.
3. Most people are innumerate or mathematically illiterate and subsequently easily fooled.
4. Keep an eye out for numbers that are surprising large or small.
5. The unit of measure is deceiving, for example using minutes to report a crime rate (% of total population)
6. All stats should be reported in simple language.
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Format: Hardcover Verified Purchase
...but it's too slight. With some judicious editing, it's a journal article. But this is a case where the complaint is not that the food was bad and the portions too small: In fact, the food was so great, one wishes it were all-you-can-eat.

And then I'm left wondering if perhaps the book's very brevity might not be part of what makes it so splendind. I have often complained that too many books are mere pamphlets exploded out to book size to make them marketable. I guess if one does not tie value to mass, then even though this book might seem too little of a good thing, it is a remarkable value for what it does contain.

What it contains, chiefly, is a compact description of several particular species of stat problem (and ultimately, sign of a healthy stat) to watch out for, followed by an example of such a stat's use from real life. In this regard, it follows pretty literally its description as a "field guide," and the samples selected are key to what makes this book excellent.

I am not confident that after reading this book I will be as good at teasing out the issues as Best and other statisticians are, but he has tried to give me some tools to recognize some of the more egregious examples of number abuse. As someone who has long struggled with numeracy and come to see just how crucial it is for a rounded understanding of science and politics and other key subjects, I am grateful for the assistance such a guide provides. I think "Spotting" is a terrific book for people who find themselves in a similar position.
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Format: Hardcover Verified Purchase
One of the most important things one can do in this time of too much information is to be able to evaluate the information being presented to you. Stat-Spotting delivers by giving you tools and yardsticks to use in evaluating statistical and numerical information presented in the plethora of sources available to someone researching a topic.

This is a book that I suggest everyone read...
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Format: Hardcover
This is a fine little--not including the acknowledgements, footnotes, and index, it's just 114 pages--book. It would be useful as a supplementary text in any statistics or quantitative methods course. It also could be enjoyed by anyone with an interest in data, especially when data are used to formulate public policy. The author, Joel Best, succinctly states his theme as follows (p. 5):

"This book is guided by the assumption that we are exposed to many statistics that have serious flaws. This is important, because most of us have a tendency to equate numbers with facts, to presume that statistical information is probably pretty accurate information. If that's wrong--if lots of the figures--that we encounter are in fact flawed--then we need ways of assessing the data we're given."

Best makes his case through a set of well-chosen examples. Some are of numbers that are inaccurately high. He warns (p. 11), ". . . keep in mind one rule of thumb: in general, the worse things are the less common they are. . . . Most social problems display this pattern: there are lots of less serious cases, and relatively few very serious ones. This point is important because media coverage and other claims about social problems often feature disturbing typifying examples: that is, they use dramatic cases to illustrate the problem."

Here are three examples.

Page 10: a claim that "more than four million women [in the U.S.] are battered to death by their husbands or boyfriends each year". Best notes that four million is far more than the annual deaths of women from all causes. I found this claim repeated in other places such as here and here. How did this claim come about? Best doesn't speculate but I found sites claiming four million batterings but not deaths: [...] and [...
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