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10 of 10 people found the following review helpful
4.0 out of 5 stars Mixed opinion, 17 Jan. 2012
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I have to agree with a lot of the US reviews. I am missing a focus in the book.

The author wants to make a point how important it is to understand the math behind real world problems, but I was disappointed by his attempts to convey mathematical principles. Formulas may work for some people, to me the book failed to point out why they are necessary - or how i can add value with them in the analyses i do. In this regards, the author overpays his dues to his academic background. I can see how the author studied physics and addresses people with like-wise framed minds. But for these people, the book will be too trivial. The major disappointment for me was that the book failed to live up to its expectations regarding the subtitle "with open Source tools". I would have expected a range of cool tools to work with, instead it's GNU and R, and there is not a single end-to-end case of getting the data, figuring out the issue and then presenting it in a graph. Sometimes, the style is too conversational, sometimes it is too strict and abstract. There are few moments when the two extremes touch. Other parts of the book - were the author shares his academic insights - felt awkward. The statement "You will never understand what mathematics is if you see it only as something you use to obtan certain results" will definitely find its way in my "Dictionary of Received Ideas".

Still after all this negative criticism, I am giving it an average 4 stars. Why? There were some conversational parts that are helpful. This happens especially when the author highlights pitfalls and real-world application on distribution laws and showing/interpreting graphical analysis (although he doesn't point out how it's done). I can put these ideas to use, and they are valuable, because they show the true expertise of the author and can serve as a guideline for people learning to get familiar with advanced statistical analysis. And I want to give credit to the broad scope of the book. I prefer this to textbooks that focus on one aspect only. Although the book is often too abstract, I appreciate the approach to cover many topics in 10-20 page essays.
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5 of 5 people found the following review helpful
4.0 out of 5 stars Very good, 12 Dec. 2011
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heltz (Glasgow, UK) - See all my reviews
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I you have no idea of what a statistical analysis or data analysis is and you'd like to know how to do it. This is your book.
There is not much formulas so if you want a book that gives you the mathematical basis this is not for you.
This book presents the different methods and the tools you can use to get them with some specific examples.
It is an applied book to get it on quickly.
The structure is done in a way that you can pick chapter you are interested in and come back later ofr other parts.

Definitely a good purchase.
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Data Analysis with Open Source Tools
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