I just finished reading this book in five hours. I haven't put it aside. For other reasons one might would imagine.
Of course, for somebody who has already received training in statistical methods, there is nothing in this book from a scientific and educational point of view. And for those who have a phobia of maths: Don't worry, there is not a single equation to find.
But that somebody would be me. Still, I couldn't put it aside. And I just wish I had read this book earlier. Because if I had, statistics would have become a serious endeavor of mine. If there is a book out there putting in plain text why statistics are important not only to those who try to do serious academic research, it is definitely this one.
Why did I subtract a star? At some point this book becomes kind of redundant. For those willing to skip pages filled with information they already digested not a problem.
But to sum it up: Fun to read, especially as a primer for statistics classes. Nothing that helps you through those classes except for lots of motivation. And you might suddenly understand why _this_ review is showed to you, not any other.
By purchasing this book I was hoping to be exposed to the way quantitative methods are used (as a tool!) in various fields. Alternatively I hoped to be exposed in an intuitive way to some breakthrough methods. However, all throughout the text the author opposes 'intuitivists' vs 'number crunchers' via selected examples. I find this opposition misleading because as far as most of the models from this book are concerned, 'garbage in ' garbage out' applies. That is to say that these models are made to test hypotheses, therefore it is not exact to oppose intuition to quantitative methods. Thus it is even more inexact to make the point that number crunching is superior to intuition. Another weak point of the book is that as introductory as it might be only 6 pages out of 220 pages discuss Bayesian methods and they are to be found at the very end of the book. However, this book provides an excellent discussion on evidence based medicine. Another very interesting part is the one where the authors points out the factors that facilitate number crunching. In a nutshell, if you know what 'significantly different from zero' and 'everything else being equal' mean, you should be able to find a better use of your time.
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I had to buy this for class. It provides a lot of examples of good uses of data mining/statistical analysis. It doesn't go into extreme detail as it is really an overview of many uses. Because of this, it's a great introduction and eye-opener on super crunching.
Sehr lesenswert, kurzweilig geschrieben, viele praktische Beispiele und absolut am Zahn der Zeit :-) Der Leser/ die LEserin wird beeindruckt sein, welche schönen Dinge die Menschheit und Forschung heute in der Lage ist zu analysieren und zu verbessern