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 figu...
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| Main Author: | |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge :
Cambridge University Press,
2016.
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| Subjects: | |
| Online Access: | CONNECT |
| Summary: | 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 mind-set of a data scientist can expose truthiness, nonsense, and outright deception. Using the tools of causal inference he evaluates the evidence, or lack thereof, supporting claims in many fields, with special emphasis in education. This wise book is a must-read for anyone who has ever wanted to challenge the pronouncements of authority figures and a lucid and captivating narrative that entertains and educates at the same time. |
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| Item Description: | Title from publisher's bibliographic system (viewed on 10 Dec 2015). |
| Physical Description: | 1 online resource (xviii, 210 pages) : digital, PDF file(s). |
| ISBN: | 9781316424315 (ebook) |
