Nate Silver’s new book is required reading for decision coaches. Nate Silver is a Bayesian. He is also bringing structured modeling and probabilistic thinking to the world of political pundits and pollsters. The title of his new book is, “The Signal and the Noise: Why So Many Predictions Fail — But Some Don’t.”
The Economist book review says,
” Nate Silver serves as a sort of Zen master to American election watchers. While pundits rake over opinion polls, economic data and the other daily flotsam of election campaigns, only to ditch yesterday’s analysis when tomorrow’s froth turns up, Mr. Silver’s Blog, FiveThirtyEight radiates a serene calm, adjusting its forecasts only when the data allow. This year that has not happened often: the predictions probided by Mr. Silver’s model expressed a probabilities, have barely shifted during much of the presidential campaign, despite events seen by some analystes as potential game-changers, such as the Supreme Court’s backing for Barack Obama’s health-care plan or Mitt Romney’s decision to appoint Paul Ryan as his running mate. Only recently, after the party conventions, has the model begun to show Obama opening up a wider lead.”
The Signal and the Noise is a book about prediction, not politics. Prediction and forecasting has always been in a sorry state. Important events like the housing crash don’t make it onto the popular radar screen even though there are warnings by wise people. Economic forecasters and rating agencies continue with their precise estimates of important variables like next month’s unemployment and interest rates. The press and the public gobble up the precise estimates as though they were based on the laws of physics.
Silver reviews the work of psycologist Philip Tetlock who has studied the predictions of political pundits. Silver elevates one kind of forecaster, “the fox,” over another, “the hedgehog.” See the differences in the table on the left. Decision coaches can help teams and decision makers by playing the role of the “fox.”
Silver believes in the value of expressing expert judgment as probabilities. Further, he believes in updating probabilities in a normative way. He does a nice job of explaining the Bayesian philosophy and demonstrates its power with several examples in the book.
As decision coaches we need to know how to express the uncertainty in the predictions we use. True to Bayes’ Rule we need to be able to update forecasts as facts and circumstances change. We need to encourage teams to see the world from multiple viewpoints. The more we can do these things the more useful we will be.
This is an important, entertaining book. I hope you enjoy it.
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