The Art of Statistics: How to Learn from Data

by David Spiegelhalter

Hardcover, 2019

Call number

519.5 SPI

Collection

Publication

Basic Books (2019), 448 pages

Description

Shows how to apply statistical reasoning to real-world problems. This isn't simply memorizing formulas or using the tools in a spreadsheet: he emphasizes the importance of clarifying questions, assumptions, and expectations, and--more importantly--knowing how to responsibly interpret the results the software generates. "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." --… (more)

User reviews

LibraryThing member thcson
After being disappointed by a couple of other statistics books for general audiences (Stigler's Seven Pillars of Statistical Wisdom and Abelson's Statistics as Principled Argument), I finally found what I was looking for. The first few chapters were a bit on the simple side but certainly
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entertaining enough to keep my interest up. For me the real rewards were in the later parts of the book where the author discusses slightly more advanced topics such as P-values, confidence intervals and Bayesian inference. I had briefly acquainted myself with these topics in my university studies but did not really understand their meaning back then. Without going into their mathematics, the author provides a nice overview of what these statistical concepts mean and what they don't mean, what they can be used for and what they cannot be used for. This somewhat philosophical review of practical statistical methods should be very useful for anyone who wants to be able to judge statistical conclusions critically. In the final chapters of the book the author also discusses how scientists sometimes misuse statistical methods, how such misuse can be detected and how newspapers and their readers should understand new scientific results when they are expressed in terms of statistics. All of which is very interesting, so I recommend this book.
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Awards

Pages

448

ISBN

1541618513 / 9781541618510
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