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Showing 1-10 of 53 reviews(Verified Purchases). See all 147 reviews
on June 20, 2015
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. Super Crunchers is that easy way! Below I have summarized some of the important points of the book....

Super Crunching is crucially about the impact of statistical analysis on real-world decisions. Two core techniques for Super Crunching are the regression and randomization.

1. Regression will make your predictions more accurate (Historical approach):

It all starts with the use of regressions, and although this method is a basic statistical test of causal relationship it's still a very powerful tool that I need to re-introduce in my analytical life.

Regressions make predictions and tell you how precise the prediction is. It tries to hone in on the causal impact of a variable on a dependent. It can tell us the weights to place upon various factors and simultaneously tell us how precisely it was able to estimate these weights.

2. Randomization and large sample sizes (Present/Real-Time approach):

Reliance on historical data increases the difficulty in discerning causation. Large randomized tests work because the distribution amongst the sample are increasingly identical. Think A/B testing on steroids that allows you to quickly test different combinations! Boils down to the averages of the "treated and untreated" groups.

Government has embraced randomization as the best way to test what works. Statistical profiling led to smarter targeting of government support

With finite amounts of data, we can only estimate a finite number of causal effects

3. Neural network
Unlike the regression approach, which estimates the weights to apply to a single equation, the neural approach uses a system of equations represented by a series of interconnected switches.

Computers use historical data to train the equation switches to come up with optimal weights. But while the neural technique can yield powerful predictions, it does a poorer job of telling you why it is working or how much confidence it has in its prediction.

Super Crunching requires analysis of the results of repeated decisions. If you can't measure what you're trying to maximize, you're not going to be able to rely on data-driven decisions.

We humans just overestimate our ability to make good decisions and we're skeptical that a formula that necessarily ignores innumerable pieces of information could do a better job than we could.
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on June 12, 2015
Overall the book is very entertaining and instructive about the way analysis of large data sets is changing our social and economic landscape. The author shares some deep insights, even for someone experienced in data analysis.

The author makes some logical missteps though. when referring to Sherlock Holme's method as deduction (instead of a combination of induction and abduction), and assuming a normal distribution in asset markets (which has been shown to be a poor model for asset prices). It's a bit nitpicky to be sure, which one might let pass for a book on a different topic, but very strange mistakes to make for a book on data science.

Great, quick read otherwise!
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on November 18, 2013
Thinking by numbers is the new way to be smart - I dig it.

Between this book and the Numerati, I feel really smart and also super sketched out by everyone knowing what I buy.

Probably should stop leaving reviews.

just sayin'.
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on February 1, 2008
I'm now inclined to be scared after reading this. Data mining, data "mashups", pervasive digital surveillance...that's what this book is about. I'm no Luddite. I love all my electronic goodies and the benefits of digitization. For example, I like Amazon's ability trecommend fairly good product matches for me based on my reading and similarities to other customers. I like scanning technology to speed me through check out lines. But after reading this book and seeing the potential impacts to our privacy and to our lives, I'm feeling more pessimistic about the unfettered direction the technology is taking us. Marketers, like Amazon and the businesses using scanners, are mining our lives for all they are worth. More than you are aware of.

Decision makers like physicians are very soon to be replaceable with artificial intelligence. Good or bad? Good if you are the patient because of better decision making. Bad if you are the physician. You can be replaced by techs in the near future. Movie producers...your go/no go "greenlight" decisions can better be made by a data mining analysis approach. Authors? Better watch out...the publisher may soon make decisions about your books based on their digital rating as potential best sellers. Almost any job requiring expert decision making is subject to increasing data analysis that is better than the experts can deliver. Scary that even creative professions are vulnerable. Customers probably will benefit from the application of the "super crunching" approach, but something may be lost (such as professional decision making jobs?). And this trend seems to be exponential as data storage becomes commoditized and processor speeds increase. Anything that can be stored as data can be "mashed up" and mined for mathematical predictive relationships. Since most of us are unaware of the acceleration of this approach, we really can't see the implications until they are on us. Where goeth free will if everything is digitized, predicted, and manipulated?

This book is not for mathematicians. It is for the lay reader. Marketers and business people who aren't aware of these trends will be excited by their potential for use in their own industries. The writing is clear but unexceptional. But the book is incredibly thought provoking if you haven't been aware of the trends. The author, who is a data miner himself, is enthusiastic about the "New Way to Be Smart" and the potentials for vastly improved decision making that can enhance our lives, but we non-crunchers need to be aware of potential freedoms unwittingly given away.
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on August 18, 2013
As an open source consultant getting into the Big Data and Analytics-field, this books was an inspirational read about how "thinking by the numbers" really is the new way to be smart, and with hands-on examples about how bad things can go when we leave the decisions to our own device.

You won't find anything ground breaking stuff here, but I can assure you that you will find the nuts and bolts of analysis, backed up with stories from the real life.

It is an easy read who also gives you a few pointers as to what other literature to read. I can highly recommend it.
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on April 9, 2013
"Tried and True" vs Innovative
"Rule of Thumb" vs Scientific Method
"Gut Hunch" vs Verifiable Methodology

If you are on the left side of each of these pairs - read this to see why "the other side" can be very helpful.
If you are on the right side of each of these pairs - read this to see why maybe "vs" should at least be "and" - using scientific method and techniques to quantify or revise the best guesses of "the experts" - combining factors that the experts consider in ways that produce repeatable and verifiable results - from baseball to wine and farther afield.
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on January 30, 2017
Despite being nearly a decade old now, it's a great book for a general background in the world of big data. Interesting to see how things have changes since then. For example a TB is not nearly as impressive as it was when this book came out!
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on January 15, 2017
I am not a statistician but I found this book very enlightening if not, at time, disconcerting. While Super Crunching is here to stay it is frightening what is known about each individual.
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on October 21, 2015
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 use it.
All-in-all, I thought this book was okay. Interesting, but not great.
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on March 30, 2013
This book provided for me critical, foundational background knowledge as I researched for and wrote my book (on the topic of predictive analytics). This book is an inspiration, and one of a small number of must-reads I heartily urge all creators and thinkers to pack for your next flight!

Eric Siegel, Ph.D.
Founder, Predictive Analytics World
Author, [...]
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