When would a casino stop a gambler from playing his next hand?
How could a company use statistical analysis to blackball you from the job you want?
Why should you worry when customer services pay attention to your needs?
Beginning with examples of the mathematician who out-predicted wine buffs in determining the best vintages, and the sports scouts who now use statistics rather than intuition to pick winners, Super Crunchers exposes the hidden patterns all around us. No businessperson, academic, student, or consumer (statistically that's everyone) should make another move without getting to grips with thinking-by-numbers - the new way to be smart, savvy and statistically superior.
Super Crunchers: How Anything Can Be Predicted
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Groundbreaking ... Not only is it fun to read. It just may change the way you think'
(Stephen D Levitt co-author of Freakonomics )'Entertaining and enlightening'
(Financial Times )'Convincing'
(Economist )About the Author
Ian Ayres is a professor at Yale, both in the Law School and in the School of Management, as well as a lawyer and author. He is a regular commentator on National Public Radio in America and a columnist for Forbes magazine. A contributor to the New York Times and editor of the Journal of Law, Economics and Organization, he has written eight books.
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7 of 7 people found the following review helpful
By Rolf Dobelli
TOP 500 REVIEWER
Format:Hardcover
"There are three kinds of lies," said Benjamin Disraeli, "lies, damned lies and statistics." But, like it or not, the world is becoming more quantitative every day and no one can afford to be statistically innumerate. If you live in Excel and use quantitative techniques daily, this may come as no surprise. What may be surprising, even to data-heads, is the extent to which statistical methods are illuminating areas of human life hitherto relegated to "experts." Call it the new age of empiricism or the rise of numerical "super crunchers," but, whatever the name, the trend is real. In this book, Yale law professor and econometrician Ian Ayres provides an unbiased sample of entertaining anecdotes showing how quantitative thinkers are taking over and why the trend is unlikely to abate. The caveat: as the world and its feedback loops get increasingly complex, is regression less useful? If so, Ayers is a bit optimistic. Yet, getAbstract finds that his book, as well as being entertaining and vigorously written, offers a painless review of important statistical ideas that even Disraeli would've found hard to challenge.
5 of 5 people found the following review helpful
Format:Paperback|Amazon Verified Purchase
I came across a reference to this book in a news article about Epagogix, a company that analyses some of the characteristics of film scripts in an attempt to identify whether a film will be successful or not. The author uses Epagogix as an example of the way in which simple statistical models are increasingly being applied to large data sets in order to improve decision making in a range of business and social applications. The interesting point is that the models often outperform the judgement of human experts in tasks such as pricing airline seats, diagnosing and treating disease, finding a life partner and paroling prisoners.
One of the other example tasks he cites is the choice of book titles, and demonstrates it with an account of how he used the statistical technique of randomized testing with Google AdWords to choose between "The End of Intuition" and "Super Crunchers", based on the number of clicks each received. This - perhaps inadvertently - isn't really a good advert for the technique, since the former title actually means something, while the one he ended up using doesn't (what's the difference between a super cruncher and a regular, standard, non-super cruncher anyway?).
However, its use is in keeping with the author's breezy, non-technical style (e.g. "He's the kind of guy that would quickly disabuse you of the notion that number crunchers are meek, retiring souls. I've seen [him] stride around a classroom, gutting the reasoning behind a seminar paper with affable exuberance" [p2]) that tries to spice up what could have been a dull subject in other hands. Thus, he describes the techniques - regression analysis and randomized testing - briskly without any mathematics (there are only a couple of diagrams in the entire book) before moving onto stories about their application. Most of the technical detail and justification has been moved to a notes section that takes up more than a tenth of the book.
I enjoyed reading this account, particularly his exploration of why this sort of thing is becoming more widespread (increasing computer power, cheaper storage, wider accessibility via the internet) and its implications for privacy and control. Those who found Freakonomics stimulating will, I think, like this as well (it should be noted that the present author has worked with one of that book's coauthors - in the past), since it provides some intriguing insights into the way in which trends in the world and our behaviour in it can be unraveled and predicted.
One of the other example tasks he cites is the choice of book titles, and demonstrates it with an account of how he used the statistical technique of randomized testing with Google AdWords to choose between "The End of Intuition" and "Super Crunchers", based on the number of clicks each received. This - perhaps inadvertently - isn't really a good advert for the technique, since the former title actually means something, while the one he ended up using doesn't (what's the difference between a super cruncher and a regular, standard, non-super cruncher anyway?).
However, its use is in keeping with the author's breezy, non-technical style (e.g. "He's the kind of guy that would quickly disabuse you of the notion that number crunchers are meek, retiring souls. I've seen [him] stride around a classroom, gutting the reasoning behind a seminar paper with affable exuberance" [p2]) that tries to spice up what could have been a dull subject in other hands. Thus, he describes the techniques - regression analysis and randomized testing - briskly without any mathematics (there are only a couple of diagrams in the entire book) before moving onto stories about their application. Most of the technical detail and justification has been moved to a notes section that takes up more than a tenth of the book.
I enjoyed reading this account, particularly his exploration of why this sort of thing is becoming more widespread (increasing computer power, cheaper storage, wider accessibility via the internet) and its implications for privacy and control. Those who found Freakonomics stimulating will, I think, like this as well (it should be noted that the present author has worked with one of that book's coauthors - in the past), since it provides some intriguing insights into the way in which trends in the world and our behaviour in it can be unraveled and predicted.
6 of 7 people found the following review helpful
Format:Paperback
"Super Crunchers" is a breezy and somewhat glib account of how quantitative methods are replacing traditional expert judgement. The author, Ian Ayres, is a law professor at Yale University that often has used quantitative methods in his research, some of which has been conducted in co-operation with Steven D. Levitt of "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" fame.
In this age of plenty when it comes to computing power and information, traditional quantitative methods for decision-making such as regressions and randomised trials are spreading to new fields. A regression on meteorological data performed by Orley Ashenfelter is a better predictor of the eventual price of Bordeaux vintages that the expert judgement of Robert Parker. In the USA government is using randomised trials to judge the efficacy of government programs. Ayres also mention methods such as neural networks that can be used to find patterns in data.
The advent of "super crunching" has its downsides. It will automate decision-making, reducing the scope for judgement in many white collar jobs. Loan officers at banks these day do little more than feed the computer with information. There is a movement for evidence-based medicine where doctors are aided by computers in the diagnoses of patients. Even jobs such as teaching could turn out to be less interesting in the future. In the USA some schools have adopted Direct Instruction, where the entire lesson is scripted, the script having been developed and tested using quantitative methods.
In the beginning of the book Ayres seems quite unconcerned about privacy, but this is dealt with in a later stage of the book. What he never really handles are the limitations of the methods he touts. Statistics is a hard tool to master, witness the many mistakes in scientific papers. Data-snooping biases is a real danger in data mining, when testing a huge number of hypotheses some are bound to pass conventional tests for statistical significance by pure chance. A hilarious riposte to evidence-based medicine was an article in the BMJ where they found that there were not enough data to support the hypotheses that parachutes are effective in preventing major trauma related to gravitational challenge.
Despite this the book is well worth a read. It is funny and interesting. If you are interested in super crunching methods in a business setting, you might want to read "Competing on Analytics: The New Science of Winning" by Thomas H. Davenport and Jeanne G. Harris.
In this age of plenty when it comes to computing power and information, traditional quantitative methods for decision-making such as regressions and randomised trials are spreading to new fields. A regression on meteorological data performed by Orley Ashenfelter is a better predictor of the eventual price of Bordeaux vintages that the expert judgement of Robert Parker. In the USA government is using randomised trials to judge the efficacy of government programs. Ayres also mention methods such as neural networks that can be used to find patterns in data.
The advent of "super crunching" has its downsides. It will automate decision-making, reducing the scope for judgement in many white collar jobs. Loan officers at banks these day do little more than feed the computer with information. There is a movement for evidence-based medicine where doctors are aided by computers in the diagnoses of patients. Even jobs such as teaching could turn out to be less interesting in the future. In the USA some schools have adopted Direct Instruction, where the entire lesson is scripted, the script having been developed and tested using quantitative methods.
In the beginning of the book Ayres seems quite unconcerned about privacy, but this is dealt with in a later stage of the book. What he never really handles are the limitations of the methods he touts. Statistics is a hard tool to master, witness the many mistakes in scientific papers. Data-snooping biases is a real danger in data mining, when testing a huge number of hypotheses some are bound to pass conventional tests for statistical significance by pure chance. A hilarious riposte to evidence-based medicine was an article in the BMJ where they found that there were not enough data to support the hypotheses that parachutes are effective in preventing major trauma related to gravitational challenge.
Despite this the book is well worth a read. It is funny and interesting. If you are interested in super crunching methods in a business setting, you might want to read "Competing on Analytics: The New Science of Winning" by Thomas H. Davenport and Jeanne G. Harris.
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Most Recent Customer Reviews
5.0 out of 5 stars
Enjoyable and thought-provoking
I'm far from an expert in this field so can't make any comment on whether the contents of the book are accurate, but I found it very engaging to read, enjoyable, and certainly got... Read more
Published 2 months ago by TimG
5.0 out of 5 stars
Nice
If you know some basic statistics there is not much new here in terms of new methods. What makes the book interesting is the way the internet and the world in general produces... Read more
Published on 30 Dec 2010 by A reader
3.0 out of 5 stars
an extended magazine article
It is fun and well written and I certainly learnt something from it.
However it just doesn't go into enough detail. It is just like an extended article in a magazine.
However it just doesn't go into enough detail. It is just like an extended article in a magazine.
Published on 1 Dec 2009 by The Emperor
2.0 out of 5 stars
Disappointing
There are many books around about how econometrics and statistical analysis are used in the modern world, often in areas you may not expect. Read more
Published on 28 Jun 2009 by Mr. G. P. Hunt
5.0 out of 5 stars
An introduction to a new world of doing business
Although this book is not for everyone, those with an interest in the commercial application of what can be done (and what is already being done) with vast amounts of data, will... Read more
Published on 7 April 2009 by Yannis Anastasakis
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