Customer Rating: 
Summary: SuperCrunchers Too Basic
Comment: Ayres, a law professor and econometrician, eschews the subjective for the objective. As he writes, "we are in a historic moment of horse vs. locomotive competition, where intuitive and experiential expertise is losing out time and time again to number crunching."
Most of the book covers dozens of examples where randomized testing provided statistically improved results in fields a diverse as charitable fundraising, internet dating, baseball drafting, and medical diagnosis. In Ayres view of the world, the role of the expert is to inform the process of statistical testing, model building and analysis. Once the original analysis is completed, decision-making becomes an automated process that can be performed by anyone with access to the model or decision tree.
Super Crunchers never teaches us how to "think-by-the numbers." While it provides many valid examples of data mining, it seldom provides the reader with the tools or the background to do any sort of meaningful analysis on his or her own. Even such basic concepts such as probability distribution and standard deviation are saved for the final chapter of the book. And this is perhaps slightly disappointing, given that Ayres provides so many delightful examples. As such, Super Crunchers is perhaps more inspirational than instructive.
Customer Rating:
Summary: Bloated Introduction to Statistics
Comment: This book is a typical example of a simple concept usually found in "Introduction" chapter on statistics book, and blown into a book of its own.
If you squeeze all the water out of Super Crunchers, it will turn into just that: a good one-page answer to "What Statistics is Good for?" question. I would recommend this book to any 19 year old thinking of taking statistics class in college, although he or she could safely stop after about 40 pages.
There is no substance, no story, no conclusion and no "main point" in it. The book reads as glorified hype of something old and trivial. The author never mentions cases when statistics gives incorrect answers due to incomplete data or unknown confounding variables, yet any statistician will tell you it happens all the time. He tells stories with doctors getting it wrong, but doesn't mention hundreds of flawed statistical studies where "super crunchers" got it wrong, except for one case where "the other guy" appears to be his colleague-opponent, and that part reads like a pathetic gossip intended for a limited audience.
This book reminds me of "Long Tail", a very similar bloated "book" about trivial and obvious matter. Every once in a while a man just wants to write a book about something, wants it real bad, but falls short of picking a good "something". Not every subject is worth a book, Ian. Sometimes a short article or a blog post will do better.
Customer Rating:
Summary: Inside empirical data-crunching
Comment: "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.
Customer Rating:
Summary: Applied Analytics
Comment: The book was written at a more hands-on level than Competing on Analytics. Also, unlike Freakonomics which showed many random relationships, this book deals with issues that business people will see everyday. I wrote down several ideas on ways to improve my own company based on concepts mentioned in this book.
Customer Rating:
Summary: The ideas in the book helped me to work smarter, not harder
Comment: I thought this was one of the best books I've read this past year. I found it to be well written, entertaining and insightful. The author's main point is that people often put way too much emphasis on their intuition and ability to predict outcomes when computer models based on historical data analysis are often much more accurate.
One of the main targets of the book is the health care industry in the U.S. and how doctors especially place too much emphasis on their own analytical skills and not enough emphasis on data. I suspect at least some of the negative reviews here are from people in the health care industry. There are good reasons why health care in the U.S. is the most expensive in the world, yet according the World Health Care organization in terms of quality of health care, it ranks at number 37, between Costa Rica and Slovenia. An industry mindset that lacks a history of taking advantage of number crunching and thinking by the numbers may well be part of the problem.
I am self employed and since reading this book I've been more numbers oriented and have been more careful to track my hours and keep very detailed logs of what activities make the most money. It has worked out well, so for me reading this book was a great investment and well worth the price of the book.
Summary: SuperCrunchers Too Basic
Comment: Ayres, a law professor and econometrician, eschews the subjective for the objective. As he writes, "we are in a historic moment of horse vs. locomotive competition, where intuitive and experiential expertise is losing out time and time again to number crunching."
Most of the book covers dozens of examples where randomized testing provided statistically improved results in fields a diverse as charitable fundraising, internet dating, baseball drafting, and medical diagnosis. In Ayres view of the world, the role of the expert is to inform the process of statistical testing, model building and analysis. Once the original analysis is completed, decision-making becomes an automated process that can be performed by anyone with access to the model or decision tree.
Super Crunchers never teaches us how to "think-by-the numbers." While it provides many valid examples of data mining, it seldom provides the reader with the tools or the background to do any sort of meaningful analysis on his or her own. Even such basic concepts such as probability distribution and standard deviation are saved for the final chapter of the book. And this is perhaps slightly disappointing, given that Ayres provides so many delightful examples. As such, Super Crunchers is perhaps more inspirational than instructive.
Customer Rating:
Summary: Bloated Introduction to Statistics
Comment: This book is a typical example of a simple concept usually found in "Introduction" chapter on statistics book, and blown into a book of its own.
If you squeeze all the water out of Super Crunchers, it will turn into just that: a good one-page answer to "What Statistics is Good for?" question. I would recommend this book to any 19 year old thinking of taking statistics class in college, although he or she could safely stop after about 40 pages.
There is no substance, no story, no conclusion and no "main point" in it. The book reads as glorified hype of something old and trivial. The author never mentions cases when statistics gives incorrect answers due to incomplete data or unknown confounding variables, yet any statistician will tell you it happens all the time. He tells stories with doctors getting it wrong, but doesn't mention hundreds of flawed statistical studies where "super crunchers" got it wrong, except for one case where "the other guy" appears to be his colleague-opponent, and that part reads like a pathetic gossip intended for a limited audience.
This book reminds me of "Long Tail", a very similar bloated "book" about trivial and obvious matter. Every once in a while a man just wants to write a book about something, wants it real bad, but falls short of picking a good "something". Not every subject is worth a book, Ian. Sometimes a short article or a blog post will do better.
Customer Rating:
Summary: Inside empirical data-crunching
Comment: "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.
Customer Rating:
Summary: Applied Analytics
Comment: The book was written at a more hands-on level than Competing on Analytics. Also, unlike Freakonomics which showed many random relationships, this book deals with issues that business people will see everyday. I wrote down several ideas on ways to improve my own company based on concepts mentioned in this book.
Customer Rating:
Summary: The ideas in the book helped me to work smarter, not harder
Comment: I thought this was one of the best books I've read this past year. I found it to be well written, entertaining and insightful. The author's main point is that people often put way too much emphasis on their intuition and ability to predict outcomes when computer models based on historical data analysis are often much more accurate.
One of the main targets of the book is the health care industry in the U.S. and how doctors especially place too much emphasis on their own analytical skills and not enough emphasis on data. I suspect at least some of the negative reviews here are from people in the health care industry. There are good reasons why health care in the U.S. is the most expensive in the world, yet according the World Health Care organization in terms of quality of health care, it ranks at number 37, between Costa Rica and Slovenia. An industry mindset that lacks a history of taking advantage of number crunching and thinking by the numbers may well be part of the problem.
I am self employed and since reading this book I've been more numbers oriented and have been more careful to track my hours and keep very detailed logs of what activities make the most money. It has worked out well, so for me reading this book was a great investment and well worth the price of the book.
Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart Reviews: Page 4 of 14
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