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Review for The Signal and the Noise: Why So Many Predictions Fail--but Some Don't
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Lively statistics
This book explains the unerring accuracy for Nate SIlver's election predictions using Bayesian statistics. The BEST part of the book for me was that I finally understand Bayes' analysis. I used quite a few sophisticated statistical tools in my work (retired as reliability physics expert for semiconductor devices, aka chips), but I was never able to grasp Bayes Theorem until now. Wikipedia's "tutorial" was far too complicated even for a PhD, but Nate provided a simple version that a layman can understand ... and he did it using a hilarious example (look for "cheating"). In fact, I am so impressed with Bayes' analysis that I am thinking about writing a corollary to my two best technical papers grafting a Bayesian view.
Returning to the election prediction issue, consider that each poll of 1000 people has a sampling error of +-5%, easily derived from Poisson statistics. However, when one pools the results from say 25 polls (and removes bias), the sample size is increased by...
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