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Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart 1st Edition

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Ian Ayres (Author)
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Ian Ayres (Author)
3.7 out of 5 stars 143 customer reviews
ISBN-13: 978-0553805406
ISBN-10: 0553805401
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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: 3.7 out of 5 stars  See all reviews (143 customer reviews)
  • Amazon Best Sellers Rank: #202,188 in Books (See Top 100 in Books)

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Customer Reviews

Top Customer Reviews

2.0 out of 5 starsCRUNCHING on Empty, CRUNCHING Blind (Apologies to Jackson Browne)
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.Read more ›
6 Comments 311 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
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1.0 out of 5 starsDisappointing
By Tursted Source 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!
10 Comments 254 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
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1.0 out of 5 starsSuper Disappointing
By Bruce 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.Read more ›
6 Comments 60 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
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Most Recent Customer Reviews

2.0 out of 5 starsNot a great book, not the right issue

I recommend the 2 star review by Steve Koss and the 1 star review by Tursted Source. Ayres makes many good points but the book could have been much better. Read more

Published 2 months ago by doug korty
5.0 out of 5 starsFive Stars

Was an insightful book, Thannks

Published 6 months ago by Victor L. Cook
4.0 out of 5 starsGreat book with lots of examples of real world applications

Great book with lots of examples of real world applications. Not enough explanation of the math, but it does encourage the individual to seek more information

Published 6 months ago by Amazon Customer
5.0 out of 5 starsSolid crash course

This book helped me better conceptualize stats as well as fuel my motivation to try and master it more fully.

Published 10 months ago by Jeff G
3.0 out of 5 starsOkay

I thought this book was interesting.
It begins by basically explaining number crunching and then shows a bunch of examples of number crunching and the different ways you can... Read more

Published 12 months ago by Keri
3.0 out of 5 starsThree Stars

Needs to be updated.

Published 14 months ago by Amazon Customer
5.0 out of 5 starsNot boring at all

Very interesting read. Not boring at all. Full of examples and stories.

Published 15 months ago by Lisa C.
4.0 out of 5 starsLeveraging data-driven insights are really the only way any of us...

Great book on the importance of data-driven decision making. While I have always been someone that has let the data do the talking, I haven't found an easy way to explain why. Read more

Published 16 months ago by Brian
5.0 out of 5 starsEnjoyable introduction to the power of statistics and big data

Overall the book is very entertaining and instructive about the way analysis of large data sets is changing our social and economic landscape. Read more

Published 16 months ago by Derrick
5.0 out of 5 starsSuper Crunchers does for state of the art use of ...

I'm a geek about data and statistics, and this book is definitely worth the read. What Freakonomics did for corner case statistical observations, Super Crunchers does for state of... Read more

Published 18 months ago by Ken Thompson

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