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The 9 pitfalls of data science

By: Smith, Gary.
Contributor(s): Cordes, Jay.
Publisher: Oxford : Oxford University Press, 2019Description: 256 P. ; ill., 21 cm.ISBN: 9780198844396.Subject(s): Big data | Quantitative research | Data science | Baseball regression | Brazilian Jiu-Jitsu | Coin sreaks | Credit default swaps | P-hacking | P-value | Sabermetrics | Texas Sharpshooter Fallacy | Artificial IntelligenceDDC classification: 005.7 Summary: Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best. 'The 9 Pitfalls of Data Science' shows us real-world examples of what can go wrong. Written to be an entertaining read, this invaluable guide investigates the all too common mistakes of data scientists - who can be plagued by lazy thinking, whims, hunches, and prejudices - and indicates how they have been at the root of many disasters, including the Great Recession.
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Includes bibliographical references and index.

Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best. 'The 9 Pitfalls of Data Science' shows us real-world examples of what can go wrong. Written to be an entertaining read, this invaluable guide investigates the all too common mistakes of data scientists - who can be plagued by lazy thinking, whims, hunches, and prejudices - and indicates how they have been at the root of many disasters, including the Great Recession.

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