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 enlarge | Author: Ian Ayres
Publisher: Bantam
Category: Book
List Price: $25.00
Buy Used: $8.49
You Save: $16.51 (66%)
New (42) Used (26) Collectible (2) from $8.49
Rating:  71 reviews
Sales Rank: 5464
Media: Hardcover
Edition: 1
Pages: 272
Number Of Items: 1
Shipping Weight (lbs): 1
Dimensions (in): 9.1 x 6.1 x 1.1
ISBN: 0553805401
Dewey Decimal Number: 519.5
EAN: 9780553805406
Publication Date: August 28, 2007
Availability: Usually ships in 1-2 business days
Shipping: Expedited shipping available
Shipping: International shipping available
Condition: Hardcover, with dust jacket. Dust jacket has slight shelf wear. Ships the next business day, with tracking and delivery confirmation sent to your email.
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| Customer Reviews:
Showing reviews 6-10 of 71
 Great introduction to the usage of statistical models October 21, 2007
Mariam Tariq (Sunnyvale, ca USA)
4 out of 7 found this review helpful
Statistical models have been around forever. With the Internet collecting data at every mouse click and seamlessly harnessing data from the masses, these models have taken on a new life. Companies can better understand customers including who they are and predict what they want with reasonable accuracy.
I picked up this book to better understand the utilization of data mining and applying statistical models to make predictions. The book doesn't get heavy into the math, but provides some good examples, across a number of different fields to demonstrate the application of statistics to decision making and discusses some of the related ethical issues. It is an informative, light read about a relevant business topic.
Fascinating Read September 2, 2007
William Yarberry (kingwood, tx United States)
14 out of 22 found this review helpful
Ian Ayres writes well and writes broadly. Covering everything from evidence based medicine to optimal means of customer retention, he shows how today's massive databases, combined with easy availability, enables better decision making. He also notes that above a certain volume of data, human ability to see trends and notice subtle trends becomes limited. Not so for Super crunching algorithms and statistics.
Between this book and Taleb's "Black Swan" I'm actually excited about the ablility of applied mathematics, combined with massive data and fast computers, to change the way people live.
Keep on writing Dr. Ayres -- you are good at it!
Bill Yarberry, Houston, Texas
Super Smart September 8, 2007
Steven Lubet (chicago)
4 out of 10 found this review helpful
This is a terrific book: thoughtful, insightful, informative, and wonderfully written. It is filled with great wisdom and small truths. Ayres shows how quantitative analysis can be used to improve results in fields from medicine to education to film production, but he is also candid about the pitfalls and shortcomings of statistical methods. He explains how advances in computing power can complement human judgment, and he shows how "turf protection" can prevent entrenched "experts" from accepting new proven results and new methodologies.
This book is a perfect companion to bestsellers such as "Blink," "Freakonomics," and "How Doctors Think."
Awesome. A must read. November 24, 2007
Lothario (Earth)
1 out of 5 found this review helpful
I am stunned by the negative reviews here -- I can't help but wonder if they are from "competitors" of some sort. This book was outstanding. Far, far better than the trivia of Freakonomics. Packed with great, insightful, apple-falling-on-your-head type info. Interesting, entertaining, educational.
Numbers win every time.
Making UberGeekness cool September 22, 2007
William G. Ryan (Atlanta, GA)
6 out of 12 found this review helpful
Although I work as a Software consultant professionally, I spent a good part of my grad studies on applied statistics. If you like computers and you like statistics, you can't help but love this book.
A few of the critical comments earlier mentioned the fact that BI is nowhere near the state of the examples he cites. I think this is totally unfair in that Ayres never implies that it is. in fact, his point is that by and large, Bi isn't there yet. That's why he cites examples of people doing it right.
If you've taken stats, you'll no doubt have went through that phase where you doubted the results and then as you saw more and more examples, you ultimately acknowledged that pretty much everything follows those patterns. Although it was an economist that came up with 80-20, it's a very common phrase to hear in business meetings and it's analogous to how other statistical methods work - when you get the inputs right, the models just work.
The only thing I'd complain about in this otherwise Superb book is that he does seem to gloss over how difficult collecting data can be. Many times the data just isn't there. And when it is, it's often in the form of a zillion excel spreadsheets and disparate data sources. Seldom is it just sitting in a well designed, normalized database. Even when it is, the whole issue of writing the queries can be a challenge. All of which are things you can overcome, but depending on your
starting point, each of these can be very daunting - PARTICULARLY when you are employing them at the level he talks about. Simpler things can be gotten easy and cheaply, but that certainly isn't the norm.
Recently, I was working with Microsoft on their new Business Intelligence curriculum and was very pleased to see BI getting the come-upance it deserves. Reporting for instance is being taken seriously rather than that thing that you stick the new programmers with. OLAP is now getting more mainstream as opposed to something in the realm of people with too much time on their hands. Oracle has had an emphasis on Bi via their OLAP tools for a while now. More vendors are following suit. This means that the tools are going to be there for people to use and they are getting much more powerful.
This bodes very well for data mining. And this book is full of examples of people that have done it well - as well as a ton of ideas for readers to do.
I really liked it. In fact, I couldn't have liked it much more. It was a great read and one that will keep me thinking for a while
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