Summary of Naked Statistics

Stripping the Dread from the Data

W.W. Norton, more...

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Naked Statistics book summary
Economist Charles Wheelan strips statistics to the bones so you can bypass the obfuscation and get to the facts.

Rating

8 Overall

9 Applicability

8 Innovation

8 Style

Recommendation

Economist Charles Wheelan, author of the bestseller Naked Economics, presents statistics as more than just formulas and bell curves. His manual isn’t a textbook, but it does introduce the concepts of information literacy within the context of data analysis. By using a narrative style reminiscent of a TED talk and injecting humor into his examples, Wheelan enlightens those who are unaware of the beauty of data. His clear, approachable handbook is for the general business reader, not financiers or stock traders. It’s a seriously useful book for the number-phobic, though some readers may skim rather than devour certain large sections or even whole chapters. Wheelan makes things easier by giving several chapters their own appendixes full of detailed formulas. getAbstract recommends this light-hearted, easy read to anyone seeking greater understanding of the glories of statistics, as well as the pitfalls. It’s interesting, witty and authoritative enough to be impressive without bogging down in esoteric theory.

In this summary, you will learn

  • Why understanding statistics matters
  • How to separate useful analysis from misleading information
  • What statistics can and cannot accomplish
 

Summary

“What’s the Point?”
All kinds of number-based events, such as election predictions, rely on statistical analysis. You can make more-accurate personal decisions about which companies to invest in and which teams to bet on if you understand the stats.

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About the Author

Author, professor, political candidate and economist Charles Wheelan wrote Naked Economics.


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    Wim Kloek 1 year ago
    Probably a useful book. Statistics are relevant to everyone and the main messages seem well explained (including examples). Some of the take-away messages are a bit of an overstatement:
    "Assume that all statistical facts and figures are subject to bias" should be rather an advice to always check potential biases in the selection, collection, processing and presentation of data. The statement "Statsitics never prove anything" can be easily falsified by the fact that official statistics sufficiently prove that the country Luxembourg has inhabitants on the 1st of January 2015 (you can also be too sceptical).

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