Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger - all by the time he was 30. The New York Times now publishes FiveThirtyEight.com, where Silver is one of the nation’s most influential political forecasters.
Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.
In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good - or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary - and dangerous - science.
Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.
With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential listen.
©2012 Nate Silver (P)2012 Penguin Audio
"Nate Silver's The Signal and the Noise is The Soul of a New Machine for the 21st century." (Rachel Maddow, author of Drift)
Nate Silver has done a great job in describing many aspects of probability theory. But he spent too much time on sports and gambling and not enough on Climate Change, which he got wrong.
A lot of stories and baseballs. Election, wwii and baseball. The beginning of this, that and baseball. But it's overall a little interesting read ... And baseball.
Enjoyed the book, saved me while feeling irritated commuting to work. Quite often I stayed in the car in the parking lot finishing listening to an interesting chapter.
Have you ever been curious as to why certain political officials get elected, why weather is more predictable than earth quakes, or how thinking probably can be beneficial to thinking in absolutes? Nate dives into all of these difficult questions and answers them with wonderful examples. Yes, it is complicated to understand, but that is the point of thinking probably. I enjoyed listening to this audiobook and look forward to more from Nate Silver.
Silver's explanations are clear and make sense - much more reasonable than a number of more polemical texts. He pretty much avoids "let's unmask the villain" tactics which tend to dominate a lot of economic discussionFor example, his explanation that rating agencies rated CDO's on the assumption that mortgage foreclosures were independent events when the housing bubble really made foreclosures more likely was pretty clear. He also explains the incentives of the rating agencies without casting (too many) aspersions. That kind of explanation is much more satisfying to me than witch hunts. I certainly hadn't understood that part of the story before. Fulminating about various parties' "greed" is not very interesting, unless you happen to think that greed is some new human characteristic that reared its ugly head in 2004 and caused the whole mess.
I did like the book, but I am probably going to stop reading it after Chapter 3. The author makes a good point many times, and then rams it down our throat to the point where you get sick of hearing it. I get the point, xxxx screwed up - move on...
They were easy to follow - I was a little worried having an audiobook on this topic..
Mike Chamberlain was an amazing narrator - I just realized that he wasn't the author now... He read it witha good believability that he was speaking from experience
Not at all, Its not really a story book
The book was good, but the repetitiveness just got grating... And when he started mentioning his website every couple of minutes, that was the final straw for me...
As far as I know, this book is one-of-a-kind. Nate Silver lets the sunshine in, exposing politico fakery while elevating prediction to a rigorous and transparent level.
A good defense of general skepticism and accessible explanation of the usefulness and limits of forecasting.
Money ball and similar books by Michael Lewis for making data analysis accessible.
Unintentionally hilarious name-dropping which I found more endearing than annoying. Almost like somebody told Mr. Silver to punch it up. Lots of clangingly unnecessary references to the food eaten with smart, successful people. Small price to pay for this book,though.
Nate explains things very well. Easy to listen to and you will learn a lot. You don't have to know math to enjoy this book.
Maybe - I don't tend to read books over and over again.
Not sure - he was a good narrator though.
Bayesian thinking. I've been familiar with Bayesian mathematics for a while but I'd never quite thought about applying it to probabilistic thinking the way Nate discusses it.
This book was an amazing read. Nate uses lots of great examples from a wide-variety of disciplines and professions to show the usefulness and limitations of statistics and prediction models.
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