Truth Or Truthiness: Distinguishing Fact From Fiction By Learning To Think Like A Data Scientist
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, 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.
"This book is like the proverbial bag of potato chips. It's impossible to stop reading after just one of its fun and thought-provoking examples of statistical reasoning."
Andrew Gelman, Columbia University