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The Signal and the Noise

Why So Many Predictions Fail - but Some Don't

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The Signal and the Noise

De : Nate Silver
Lu par : Mike Chamberlain
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 NEW YORK TIMES BESTSELLER • The groundbreaking exploration of probability and uncertainty that explains how to make better predictions in a world drowning in data, from the nation’s foremost political forecaster—updated with insights into the pandemic, journalism today, and polling

One of The Wall Street Journal’s Ten Best Works of Nonfiction of the Year

“Could turn out to be one of the more momentous books of the decade.”—The New York Times Book Review

Most predictions fail, often at great cost to society, because 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.

Drawing on his own groundbreaking work in sports and politics, Nate Silver examines the world of prediction, investigating how to seek truth from data. In The Signal and the Noise, Silver visits innovative forecasters in a range of areas, from hurricanes to baseball to global pandemics, from the poker table to the stock market, from Capitol Hill to the NBA. He discovers that what the most accurate ones have in common is a superior command of probability—as well as a healthy dose of humility.

With everything from the global economy to the fight against disease hanging on the quality of our predictions, Nate Silver’s insights are an essential read. Economie Management et direction Mathématiques Politique et gouvernement Prévision et planification stratégique Élections et processus politique

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"Nate Silver's The Signal and the Noise is The Soul of a New Machine for the 21st century." (Rachel Maddow, author of Drift)
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Detecting signals takes a Bayesian approach based on continously updating predictions with experience. The book takes you there step by step through examples. I like it because it's how I've been writing AI predictive algorithms for 30+ years including planning software that is based on forecasting.

Exiting the world of certainty

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