The Signal and the Noise: Why So Many Predictions Fail--but Some Don't
Format: PDF / Kindle (mobi) / ePub
"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 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 thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of FiveThirtyEight.com.
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 read.
early-voting states like Iowa and New Hampshire that all the others drop out. Even though the candidate is far from having clinched the nomination mathematically, there may be no need for the other states to hold a meaningful vote if the candidate has demonstrated that he is acceptable to most key coalitions within the party. Such a candidate can be described as having won the nomination by consensus. Science, at least ideally, is exactly this sort of deliberative process. Articles are
question and can come up with an exact answer, that is a known known. If we ask ourselves a question and can’t come up with a very precise answer, that is a known unknown. An unknown unknown is when we haven’t really thought to ask the question in the first place. “They are gaps in our knowledge, but gaps that we don’t know exist,” Rumsfeld writes in his 2011 memoir.22 The concept of the unknown unknown is sometimes misunderstood. It’s common to see the term employed in formulations like
Union, for instance. Rather than seeing the USSR in highly ideological terms—as an intrinsically “evil empire,” or as a relatively successful (and perhaps even admirable) example of a Marxist economic system—they instead saw it for what it was: an increasingly dysfunctional nation that was in danger of coming apart at the seams. Whereas the hedgehogs’ forecasts were barely any better than random chance, the foxes’ demonstrated predictive skill. FIGURE 2-2: ATTITUDES OF FOXES AND HEDGEHOGS
393, 397–99, 401–6, 402, 507 in Google searches, 290–91 by hedgehogs, see hedgehogs human ingenuity and, 292 of Hurricane Katrina, 108–10, 140–41, 388 as hypothesis-testing, 266–67 by IPCC, 373–76, 389, 393, 397–99, 397, 399, 401, 507 in Julius Caesar, 5 lack of demand for accuracy in, 202, 203 long-term progress vs. short-term regress and, 8, 12 Pareto principle of, 312–13, 314 perception and, 453–54, 453 in poker, 297–99, 311–15
would mean between two and four million fatalities. What the Gutenberg–Richter law does not tell us anything about is when the earthquake would strike. (Nor does it suggest that Tehran is “due” for an earthquake if it hasn’t experienced one recently.) Countries like Iran and Haiti do not have the luxury of making contingency plans for a once-every-three-hundred-year event. The earthquake forecasts produced using the Gutenberg–Richter law provide for a good general guide to the hazard in an