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on 28 December 2010
Not everything in this book is bad: the historical information is very interesting. (The author has a PhD in the history of science.)

Unfortunately, however, the book is riddled with blunders and misconceptions, obfuscations and inaccuracies.

Consider just one topic: the standard deviation -- pretty important when it comes to understanding statistics.

We are told that the standard deviation 'indicates how widely or closely spread the values are in a set of a data' (fine so far, apart from the typo of an extra 'a'), and then that it 'shows how far each of these individual values deviate from the average'. No: as a single summary figure, the standard deviation cannot possibly give information on 'each of these individual values'. (That is not its purpose, of course; indeed it almost the exact opposite of its purpose.)

The accompanying graphic carries the information that the 'standard deviation ... corresponds to the moment of inertia ... of dynamics'. No: it corresponds to the radius of gyration. And we are told that the moment of inertia is 'a geometrical property of a beam, and a measure of the beam's ability to resist buckling or bending'. Oh dear! Clearly the author's grasp of mechanics is no better than her grasp of statistics.

The formula for the standard deviation is then given -- but it is typeset incorrectly!

Next, the standard deviation for a set of data (with mean 8) is calculated (correctly!) as 2.82. The accompanying comment is 'This means that the average amount of deviation in this set of data is 2.82 units away from the mean value of 8 and that, therefore, there is a small amount of variation in this sample'. There appears to be no explanation of the criterion by which the variation is deemed large or small. Certainly it is not a criterion known to this statistician.

Finally, we have 'Although the standard deviation indicates to what extent the whole group deviates from the mean, it does not show how variable a particular group is.' I have read that over and over again and I am at a loss to know what it is trying to say.

I wish I could say that the other statistical concepts in the book fared better than the standard deviation -- but they don't. I can't resist mentioning the coefficient of variation which is said to be useful in comparing the variability of temperatures in two cities, one set of measurements being in in degrees Celsius and the other in Fahrenheit. This, of course, is a perfect example of when it would *not* be appropriate to use the coefficient of variation -- because the mean could be zero and the coefficient of variation would then be infinite.

If you understand anything about statistics this book will infuriate you; if you don't understand much about statistics the book will hinder not help.

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on 8 March 2014
I really like the idea behind this series of books, I've read maybe half a dozen of them now and haven't had any complaints. However, having just read one of the reviews of this book which points out some technical problems with the content, I'm starting to have my doubts about them.

I read these books purely as an interested amateur. I like the easy-reading style which allows me to dip in and out whenever I don't feel like reading something 'heavy', yet I still feel like I'm learning something useful.

Unfortunately, some of the things you will learn when reading this book are simply wrong. The examples pointed out previously concerned standard deviation and coefficient of variation - the formulae and examples given are correct, but some of the reasoning about when they are appropriate and what they mean is incorrect.

This is a problem for me, because I think it is those aspects of statistics - what the standard deviation actually 'means' - which this sort of book should be most useful for. The calculations and formulae can be found in standard textbooks if you need them, but I want the ideas placed in some kind of context first before I dive in to the nitty gritty.

In one sense, the book succeeds - the history of the people and their ideas is (as far as I know) accurate and interesting. In another sense, the book is a failure - it misleads the unwary (i.e. me) into false understandings of important concepts.

Read it for the history of statistics, but you might want to double check anything else.
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on 8 December 2010
I bought this as a potential present for a teenage nephew. However, as a statistician I of course read it first to make sure it wouldn't mislead him. It is good on history, but there are errors in the statistical content, and the language is a bit hard for a teenager in places, so I won't be passing it on.
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