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6 of 6 people found the following review helpful
4.0 out of 5 stars An enjoyable stats primer/refresher, 16 Nov. 2013
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This review is from: Naked Statistics: Stripping the Dread from the Data (Kindle Edition)
Naked Statistics is a good way to remind yourself what statistics is about, or if new to the subject, get a solid grasp of the basics. It is a fine complement to a dry textbook, in that it covers the groundwork in a clear, approachable and entertaining way that is not overly mathematically demanding. Appendices delve deeper into theory and can be read or ignored as the reader wishes.

The first two thirds of the book is particularly good, breezing competently through key statistical concepts up to and including the Central Limit Theorem.

Many people may be drawn to the book because of the growing importance of 'big data'. Wheelan takes this topic on board with a focus on regression analysis, and is not afraid to discuss the pitfalls as well as the benefits of the more abstract 'darker' arts of statistics. However, given the choice between a candid acknowledgements of the fundamental limitations of statistics and an uncomplicated view that 'as long as its done well all will be fine', Wheelan goes in the simpler, more positive direction, even when cheerfully supporting claims that over half of the top-flight peer reviewed scientific papers that draw conclusions from the techniques he proposes are likely to be wrong.

Instead, Wheelan argues that brilliant statistical research simply requires brilliant researchers (guess who?) - and that brilliance is not about being good at the maths, but about a having a creative and intuitive grasp of what works. There are two problems with this. One is that observant readers may well spot flaws in the exemplars Wheelan presents as brilliant. The second (and more important) is that the power of statistics is meant to be its ability to reveal insights that are drawn entirely objectively, yet it is clear that many mistakes in statistical research are due to failings in the researchers' subjective and interpretive skills - in other words, the maths disappears - advanced stats is a matter of judgement (so why not rely on judgement and abandon the somewhat bogus claim of objectivity?).

Consequently (and slightly disappointingly), Wheelan's concluding chapter is all about the amazing contribution statistics will continue to make to solving the world's most pressing problems, rather than a more reflective assessment of its strengths and weaknesses.

All this said, this is a likeable and workmanlike book that treats a potentially dry subject with significant flair.
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