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Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart Hardcover – August 28, 2007

ISBN-13: 978-0553805406 ISBN-10: 0553805401 Edition: 1st

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Product Details

  • Hardcover: 272 pages
  • Publisher: Bantam; 1 edition (August 28, 2007)
  • Language: English
  • ISBN-10: 0553805401
  • ISBN-13: 978-0553805406
  • Product Dimensions: 6.2 x 1 x 9.3 inches
  • Shipping Weight: 1.1 pounds
  • Average Customer Review: 3.6 out of 5 stars  See all reviews (131 customer reviews)
  • Amazon Best Sellers Rank: #516,991 in Books (See Top 100 in Books)

Editorial Reviews

From Publishers Weekly

Yale Law School professor and econometrician Ayres argues in this lively and enjoyable book that the recent creation of huge data sets allows knowledgeable individuals to make previously impossible predictions. He calls the data set analysts super crunchers and discusses the changes they're making to industries like medical diagnostics, air travel pricing, screenwriting and online dating services. Although Ayres presents both sides of this revolution, explaining how the corporate world tries to manipulate consumer behavior and telling consumers how to fight back, his real mission is to educate readers about the basics of statistics and hypothesis testing, spending most of his time in an edifying and entertaining discussion of the use of regression and randomization trials. He frequently asks whether statistical methods are more accurate than the more intuitive conclusions drawn by experts, and consistently concludes that they are. Ayres skillfully demonstrates the importance that statistical literacy can play in our lives, especially now that technology permits it to occur on a scale never before imagined. (Sept. 4)
Copyright © Reed Business Information, a division of Reed Elsevier Inc. All rights reserved.

Review

"In the past, one could get by on intuition and experience. Times have changed. Today, the name of the game is data. Ian Ayres shows us how and why in this groundbreaking book Super Crunchers. Not only is it fun to read, it just may change the way you think."—Steven D. Levitt, author of Freakonomics

"Data-mining and statistical analysis have suddenly become cool.... Dissecting marketing, politics, and even sports, stuff this complex and important shouldn't be this much fun to read."—Wired

"[Ayres's] thesis is provocative: Complex statistical models could be used to market products more intelligently, craft better movies, and solve health-care problems—if only we could get past our statistics phobia."—Portfolio

"When statistics conflict with expert opinion, bet on statistics....Businesses, consumers, and governments are waking up to the power of analyzing enormous tracts of information."—Discover

"Super Crunchers shows that data-driven decisionmaking is not just revolutionizing baseball and business; it's changing the way that education policy, health care reimbursements, even tax regulations are crafted.  Super Crunching is truly reinventing government.  Politicians love to tout policy proposals, but they rarely come back and tell you which ones succeeded and which ones failed.  Data-driven policy making forces government to ask the bottom line question of 'What works.'  That's an approach we can all support."—John Podesta, President of the Center for American Progress

"A lively and yet rigorously careful account of the use of quantitative methods for analysis and decision-making.... Both social scientists and businessmen can profit from this book, while enjoying themselves in the process."—Dr. Kenneth Arrow, Nobel Prize winning economist, and Professor Emeritus at Stanford University

“Ayres’ point is that human beings put far too much faith in their intuition and would often be better off listening to the numbers.... The best stories in the book are about Ayres and other economists he knows, whether they are studying wine, the Supreme Court or jobless benefits.... Ayres himself is one of the [statistical] detectives. He has done fascinating research.”—The New York Times Book Review

"Ian Ayres [is] a law-and-economics guru."—Chronicle of Higher Education

“Lively and enjoyable.... Ayres skillfully demonstrates the importance that statistical literacy can play in our lives, especially now that technology permits it to occur on a scale never before imagined.... Edifying and entertaining."—Publishers Weekly

"Super Crunchers presents a convincing and disturbing vision of a future in which everyday decision-making is increasingly automated, and the role of human judgment restricted to providing input to formulae."—The Economist

"Insightful and delightful!" —Forbes

More About the Author

Ian Ayres is the William K. Townsend Professor at Yale Law School and the Yale School of Management, and is editor of the Journal of Law, Economics and Organization. In addition to his best-selling SuperCrunchers, Ayres has written for the New York Times, the Wall Street Journal, Financial Times, International Herald Tribune, and The New Republic. He lives in New Haven, Connecticut.Barry Nalebuff is Professor of Economics and Management at the Yale School of Management. His books include The Art of Strategy (an update of the best-selling Thinking Strategically) and Co-opetition. He is the author of fifty scholarly articles and has been an associate editor of five academic journals. He lives in New Haven, Connecticut.

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Customer Reviews

Not worth spending money on this book.
Milano_ice
The book stays away from politics, while Ayres points out Super Crunchers all over the country that are making changes in education, insurance, and medicine.
Michael Henshaw
This means the book would be great for most people who do not have statistics backgrounds, and might be skeptical or afraid of it.
Ouchfest

Most Helpful Customer Reviews

287 of 321 people found the following review helpful By Steve Koss VINE VOICE on November 11, 2007
Format: Hardcover
Is it a new brand of cereal? Or maybe it's a granola bar, or a chunky peanut butter spread? Then again, could it be the latest infomercial exercise device designed to give you the six pack abs you've always dreamed of but know in your heart of hearts you'll never achieve? Actually, it's a book - the title a product of the very methods the book describes. Here's what SUPER CRUNCHERS says.

(1) Mathematical regression models generated from large datasets often generate better predictions than human experts, and they provide supporting information on the predictive weight and reliability of each explanatory variable.
(2) Well-crafted experiments using randomized trials and control groups provide good market research and behavioral analysis results.
(3) Technological advances - the Internet, massive data storage devices, rapid computation, broadband telecommunication - are making it possible to share more sources of information and create ever-larger databases for analysis.
(4) Today's companies engage in multiple forms of market research by creating and using large databases and large-scale randomized trials.
(5) Many phenomena conform to normal distributions in which 95% of the population will be found within two standard deviations of the mean, the5% balance generally divided evenly in the two tails.

That's it. I just saved you $25.00 U.S. and a half-dozen or more hours learning how a guy from Yale named Ian Ayres collected a bit of information about applied mathematical techniques that have been in practical use for decades, packaged them up, palmed them off as something new, and cooked up the ridiculous name Super Crunching to describe an ostensibly new technological development.
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244 of 297 people found the following review helpful By William Addington on October 6, 2007
Format: Hardcover
I read a blurb on this book in the Economist and bought it for that reason. When I read it however, it failed to deliver. It is similar to the Tom Peter's "Search of Excellence" type book with anecdotal stories with little substance. It is overgeneralized and overhypes the models it discusses. The models Ayres discusses are also NOT NEW. I personnally have been creating these types of system for nearly 30 years. What has changed over the years, of course, is greater accessibility of data and a greater capacity to process that data economically. But we still struggle with quality of data issues and appropriateness of model issues -- especially when the models begin to be used by people other than the model creators. The book glosses over this, only providing an example of how Choicepoint used a poor matching algorithm when eliminating felons from Florida's voting roles and even then the author minimizes the problem.

There is no discussion of how these models become abused when implemented as tools where the user of the tool has no knowledge of its limitations, when the model provides suboptimal solutions or what "outliers" are and how to deal with them (although you know immediately when you ARE the outlier and are trapped dealing with a company using a model designed for a population you don't belong to).

This leads us to becoming a nation of people who read off a screen and do what the computer says to do, while turning off our brain. Any wonder you can get outsourced in that scenario? But it must be right -- we Super Crunched it!
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53 of 64 people found the following review helpful By The Professor on January 3, 2008
Format: Hardcover
Like "Freakonomics," this book over-relies on a catchy phrase as a substitute for a thorough exploration of the concepts and issues. The list of concerns includes:
1. Vague definition of the term "supercrunching." Is it "super" because the author wants us to think all statistics are super, or (what I had hoped) is there something about the type of statistics to which he refers that are in fact different from statistics in decision making for the last 40 years? All the talk of large datasets implies that supercrunching is a matter of size, but then why does the very first example of regression involve a model that has only 2 predictors? No need for large data sets for this kind of a model, right? Unless the effect size is tiny, but then, what good is the model? Tell us how things really are new and different now.
2. The book reads like a list of (mostly internet) companies and how fabulous and smart they are for using statistics. Actuarial science has been around for many, many years and again we see little discussion of how the actuarial tradition has become more available outside of the insurance industry. The whole book seems more like a stream of consciousness than an organized conceptual framework about the emergence of statistics as a guide to commercial, medical, and policy making over time.
3. While perhaps an excellent lawyer and professor, the author makes so many misleading or inaccurate remarks about statistics that it could be difficult for someone with a statistics background to enjoy the book.
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