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Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart
by Ian Ayres
from Bantam

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

 

List Price: $25.00
Price: $16.50
You save: $8.50 (34%)

Media: Hardcover
Availability: Usually ships in 24 hours

Buy from: Canada Germany France United Kingdom


Customer Reviews:

  • Avg. Customer Rating: 3.5 / 5.0

  • Entertaining, but far from super

    This is an easy and mostly entertaining read. The author uses many anecdotes to
    persuade us that statistics can be a useful tool for decision making. Some of
    the described applications use lots of data and multiple regression. Those are
    easier to do now than they used to be, because more data is collected and kept.
    Some are trivial. If your company hurts a customer, apologize. You might get
    some ideas of thing to do that might help your organization. You will not get more info

  • What you can do with large datasets
    The answer is of course: a lot.
    And Ian Ayres' book will tell you a little about it.
    Supercrunchers are those who use lage datasets
    to find patterns in human behaviour, and
    predict the future based on these large datasets.
    The book informs us that super crunching is on the verge of being
    used all over. E.g.
    Chess grandmaster Kasparov was no match
    for IBMs Deep Blue chess computer,
    that stored some 700.000 grandmaster chess games to help find the more info

  • Weak Book, not original material
    This is new? The notion that empirical research is useful has been dealt with in book after book. The book not only recycles stories word for word without quote marks from the New York Times and other publications. There are hundreds of books that show that empirical work can help understand the world. What is new? What is interesting that is new here?

  • comme ci, comme ça
    It comes on the heals of some really great non-fiction analytical books. Unfortunately, this book is all anecdotal and lacks real substance. It is good for non-mathematical, non-analytical people, but not good for people with solid educations in math, statistics, and data analysis.


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