Naked Statistics: Stripping the Dread from the Data Paperback – 18 Feb 2014
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Naked Statistics is an apt title. Charles Wheelan strips away the superfluous outer garments and exposes the underlying beauty of the subject in a way that everyone can appreciate. --Hal Varian, chief economist at Google
From the Inside Flap
"Brilliant, funny . . . the best math teacher you never had."-San Francisco Chronicle
Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called "sexy." From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.
For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.
And in Wheelan's trademark style, there's not a dull page in sight. You'll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let's Make a Deal-and you'll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.
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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.
My only criticism is that in the Kindle edition the equations themselves are unreadably small, but they are not essential for a casual reader.
I wasn't expecting much, but Wheelan blew me away with the awesomeness which he squeezed into this book. If it isn't already, this should be on the reading list of every undergraduate at University. Heck, it should be on EVERYONES' reading list! It starts with an introduction to the basics and progresses into more advanced material. All along the way, he explains all of the concepts extremely well and uses examples to get the point across. It's a shame a lot of his examples are Americanized, but you still get the point he's trying to make.
As a graduate student, I kept up with this and found it a useful refresher and something which I can revisit to clarify topics in the future on a couple of the more advanced points. But, being honest, this is approachable for anybody with an interest in statistics and its usefulness in everyday life. If you have a really basic knowledge, you might have to re-read some of the concluding chapters once or twice, but Wheelan writes very well so I wouldn't expect this to be much of a chore.
Just to conclude, it's a shame that more statistics book aren't like this. He makes a terrifying subject A LOT more approachable and something (SHOCK!) that we can find fun in! Wouldn't hesitate to recommend to anyone.
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