by Nate Silver
Insightful, interesting, and filled with interesting discussions of how predictions can fail. I really enjoyed that Nate Silver stuck to his own advice when providing ways to make more accurate predictions. He was not overconfident and did settle for one simple and right answer. This should be requi...
I love data. I thought I should just get that geeky admission out of the way since my love of this book is largely based on my love of data and the cool things we can do with it. Nate Silver is an awesome statistician best known for his model that has done a great job predicting election winners. In...
An excellent read, with very detailed insights into areas in which Silver has a wealth of personal experience, including limit Texas Hold'em, baseball statistics used in forecasting player performance, and political polling, combined with insights derived from extensive interviews with top practitio...
Way too many numbers for me.
First things first: skip the introduction. It's more boring than any other section, and all it tells is what the general outline of the book is. You can get that from the contents.This is a book which is very well-researched, and well-reasoned, with apt examples. The net result is that what Silver i...
Greatly enjoyed this book, and not just because it touches on baseball, weather, games and politics. Very savvy explanations of how too much data makes finding insights harder and not easier, and how a Bayes interpretation (properly applied) can provide the best predictions. An excellent point towar...
A very good read. The moral of the story is that we know less than we think we do, and our predictions (typically) are far less reliable than we think they are. He talks a lot about Baye's Theorem, which encourages a constant updating of how one perceives the world and the likelihood of certain ev...
A solid read on predictions, probability, and statistics, presented in such a way that even an inferior at math (such as myself) can understand. Silver beats the reader over the head with the Bayes's approach, especially in the second half, which gets repetitive and old after a while, but the book ...
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