Truth or Truthiness
Distinguishing Fact from Fiction by Learning to Think Like a Data Scientist
Teacher tenure is a problem. Teacher tenure is a solution. Fracking is safe. Fracking causes earthquakes. Our kids are over-tested. Our kids are not tested enough. We read claims like these in the newspaper every day, often with no justification other than 'it feels right'. How can we figure out what is right? Escaping from the clutches of truthiness begins with one simple question: 'what is the evidence?' With his usual verve and flair, Howard Wainer shows how the sceptical mindset of a data scientist can expose truthiness, nonsense, and outright deception. Using the tools of causal inference he evaluates the evidence, or lack thereof, suppo…
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Produktdetails
- ISBN: 978-1-107-13057-9
- EAN: 9781107130579
- Produktnummer: 19025745
- Verlag: Cambridge University Pr.
- Sprache: Englisch
- Erscheinungsjahr: 2015
- Seitenangabe: 232 S.
- Masse: H23.6 cm x B15.4 cm x D2.2 cm 459 g
- Abbildungen: 52 b/w illus, 9 colour illus, 12 tables
- Gewicht: 459
Über den Autor
Howard Wainer is a Distinguished Research Scientist at the National Board of Medical Examiners. He has published more than four hundred articles and chapters in scholarly journals and books.
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Distinguishing Fact from Fiction by Learning to Think Like a Data Scientist
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Distinguishing Fact from Fiction by Learning to Think Like a Data Scientist
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Distinguishing Fact from Fiction by Learning to Think Like a Data Scientist
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Distinguishing Fact from Fiction by Learning to Think Like a Data Scientist
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