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The Art of Statistics
Cover of The Art of Statistics
The Art of Statistics
How to Learn from Data
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The definitive guide to statistical thinking


Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence — and even more so if we hope to participate in the future, rather than being simple bystanders.


In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems — it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and — perhaps even more importantly — we learn how to responsibly interpret the answers we receive.


Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

The definitive guide to statistical thinking


Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence — and even more so if we hope to participate in the future, rather than being simple bystanders.


In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems — it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and — perhaps even more importantly — we learn how to responsibly interpret the answers we receive.


Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

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About the Author-
  • David Spiegelhalter is a British statistician and Chair of the Winton Centre for Risk and Evidence Communication in the Statistical Laboratory at the University of Cambridge. He was also elected as President of the Royal Statistical Society for 2017-18. In addition to presenting documentaries on BBC4, he has appeared on Infinite Monkey Cage, BBC Horizon, and the Life Scientific, and he has been a guest columnist in the Times, Guardian, and New Scientist. Spiegelhalter was knighted for his services to statistics in 2014. He lives in Cambridge, UK.
Reviews-
  • Kirkus

    July 1, 2019
    An exploration of "why we need statistics" and how to use them effectively. The fact that Darrell Huff's delightful How to Lie With Statistics (1954) remains in print should convince readers that politicians, demagogues, and advertisers have never had trouble misleading us with numbers and graphs. Still, the study of statistics is widely considered boring, so popular books on the subject work hard to be entertaining; this expert primer mostly measures up. Distinguished British statistician Spiegelhalter (Statistics/Univ. of Cambridge; Sex by Numbers, 2015, etc.), a former president of the Royal Statistical Society, writes that "numbers do not speak for themselves; the context, language, and graphic design all contribute to the way communication is received. We have to acknowledge that we are telling a story." Some statistics are meaningless--e.g., based on average, a human has one testicle. Some are unhelpful: Vegetarians earn more than meat-eaters, but avoiding meat is unlikely to boost your income. An identical statistic can tell a horror story--e.g., a drug increases the risk of lung cancer by 14%, or not, if it increases the risk from 1 to 1.14 in 1,000. Unlike Huff's slim volume, Spiegelhalter goes beyond debunking numerical nonsense to deliver a largely mathematics-free but often formidable education on the vocabulary and techniques of statistical science. Almost everyone will understand how "median" differs from "average," and most will grasp the meaning of a bell curve or that "deduction" (using the rules of logic to come to a conclusion, Sherlock Holmes) is the converse of "induction" (using particular events to draw a general conclusion). Despite careful explanations and a plethora of tables and graphs, readers may strain to understand concepts such as the Poisson distribution, confidence intervals, bootstrapping, or standard deviation, but their efforts will be rewarded. An admirable corrective to fake news and sloppy thinking.

    COPYRIGHT(2019) Kirkus Reviews, ALL RIGHTS RESERVED.

  • Publisher's Weekly

    July 22, 2019
    Spiegelhalter (Sex by Numbers), a University of Cambridge statistician, demonstrates in his intriguing, nontechnical primer how to reliably evaluate even the most extravagant claim. Spiegelhalter’s goal is to show readers that statistics is about more than just counting numbers. A question about what happened to children having heart surgery at a particular hospital becomes a lesson in the psychological effects of “framing” results: reporting the “mortality rate” might cause alarm, but providing a “survival rate” sounds more reassuring. From issues with pie charts and the “wisdom of crowds,” to using data distributions, modelling relationships, and the correlation/causation quandary, Spiegelhalter offers clear and surprisingly enlightening examples. Concepts including margins of error and statistical significance, he demonstrates, become vital when assessing a statistics-backed claim, such as one made by a mischievous journalist who published a paper “proving” chocolate consumption caused weight loss—the data was real, but any trained statistician could see it was statistically insignificant. Spiegelhalter’s book is both fully comprehensible and valuable in a digitally driven world in which data literacy has become newly important.

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