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The Signal and the Noise: Why So Many Predictions Fail - But Some Don't, by Nate Silver
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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
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.
- Sales Rank: #23291 in Books
- Brand: Penguin Press HC, The
- Published on: 2012-09-27
- Released on: 2012-09-27
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 9.56" h x 1.00" w x 6.38" l, 1.63 pounds
- Binding: Hardcover
- 544 pages
- Great product!
Amazon.com Review
Amazon Best Books of the Month, September 2012: People love statistics. Statistics, however, do not always love them back. The Signal and the Noise, Nate Silver's brilliant and elegant tour of the modern science-slash-art of forecasting, shows what happens when Big Data meets human nature. Baseball, weather forecasting, earthquake prediction, economics, and polling: In all of these areas, Silver finds predictions gone bad thanks to biases, vested interests, and overconfidence. But he also shows where sophisticated forecasters have gotten it right (and occasionally been ignored to boot). In today's metrics-saturated world, Silver's book is a timely and readable reminder that statistics are only as good as the people who wield them. --Darryl Campbell
From Bookforum
Silver doesn't offer one comprehensive theory for what makes a good prediction in his interdisciplinary tour of forecasting. But the book is a useful gloss on the tricky business of making predictions correctly. —Chris Wilson
Review
One of Wall Street Journal's Best Ten Works of Nonfiction in 2012
“Mr. Silver, just 34, is an expert at finding signal in noise… Lively prose — from energetic to outraged… illustrates his dos and don’ts through a series of interesting essays that examine how predictions are made in fields including chess, baseball, weather forecasting, earthquake analysis and politics… [the] chapter on global warming is one of the most objective and honest analyses I’ve seen… even the noise makes for a good read.”
—New York Times
“Not so different in spirit from the way public intellectuals like John Kenneth Galbraith once shaped discussions of economic policy and public figures like Walter Cronkite helped sway opinion on the Vietnam War…could turn out to be one of the more momentous books of the decade.”
—New York Times Book Review
"A serious treatise about the craft of prediction—without academic mathematics—cheerily aimed at lay readers. Silver's coverage is polymathic, ranging from poker and earthquakes to climate change and terrorism."
—New York Review of Books
"Mr. Silver's breezy style makes even the most difficult statistical material accessible. What is more, his arguments and examples are painstakingly researched..."
—Wall Street Journal
"Nate Silver is the Kurt Cobain of statistics... His ambitious new book, The Signal and the Noise, is a practical handbook and a philosophical manifesto in one, following the theme of prediction through a series of case studies ranging from hurricane tracking to professional poker to counterterrorism. It will be a supremely valuable resource for anyone who wants to make good guesses about the future, or who wants to assess the guesses made by others. In other words, everyone."
—The Boston Globe
"Silver delivers an improbably breezy read on what is essentially a primer on making predictions."
—Washington Post
“The Signal and the Noise is many things — an introduction to the Bayesian theory of probability, a meditation on luck and character, a commentary on poker's insights into life — but it's most important function is its most basic and absolutely necessary one right now: a guide to detecting and avoiding bullshit dressed up as data…What is most refreshing… is its humility. Sometimes we have to deal with not knowing, and we need somebody to tell us that.”
—Esquire
“[An] entertaining popularization of a subject that scares many people off… Silver’s journey from consulting to baseball analytics to professional poker to political prognosticating is very much that of a restless and curious mind. And this, more than number-crunching, is where real forecasting prowess comes from.”
—Slate
“Nate Silver serves as a sort of Zen master to American election-watchers… In the spirit of Nassim Nicholas Taleb’s widely read “The Black Swan”, Mr. Silver asserts that humans are overconfident in their predictive abilities, that they struggle to think in probabilistic terms and build models that do not allow for uncertainty.”
—The Economist
"Silver explores our attempts at forecasting stocks, storms, sports, and anything else not set in stone."
—Wired
"The Signal and the Noise is essential reading in the era of Big Data that touches every business, every sports event, and every policymaker."
—Forbes.com
“Laser sharp. Surprisingly, statistics in Silver’s hands is not without some fun.”
—Smithsonian Magazine
“A substantial, wide-ranging, and potentially important gauntlet of probabilistic thinking based on actual data thrown at the feet of a culture determined to sweep away silly liberal notions like ‘facts.’”
—The Village Voice
“Silver shines a light on 600 years of human intelligence-gathering—from the advent of the printing press all the way through the Industrial Revolution and up to the current day—and he finds that it's been an inspiring climb. We've learned so much, and we still have so much left to learn.”
—MLB.com
“Nate Silver’s The Signal and the Noise is The Soul of a New Machine for the 21st century (a century we thought we’d be a lot better at predicting than we actually are). Our political discourse is already better informed and more data-driven because of Nate’s influence. But here he shows us what he has always been able to see in the numbers—the heart and the ethical imperative of getting the quantitative questions right. A wonderful read—totally engrossing.”
—Rachel Maddow, author of Drift
“Yogi Berra was right: ‘forecasting is hard, especially about the future.’ In this important book, Nate Silver explains why the performance of experts varies from prescient to useless and why we must plan for the unexpected. Must reading for anyone who cares about what might happen next.”
—Richard Thaler, co-author of Nudge
“Making predictions in the era of ‘big data’ is not what you might imagine. Nate Silver's refreshing and original book provides unpredictably illuminating insights differentiating objective and subjective realities in forecasting our future. He reminds us that the human element is still essential in predicting advances in science, technology and even politics... if we were only wise enough to learn from our mistakes.”
—Governor Jon Huntsman
“Here's a prediction: after you read The Signal and the Noise, you'll have much more insight into why some models work well—and also why many don't. You'll learn to pay more attention to weather forecasts for the coming week—and none at all for weather forecasts beyond that. Nate Silver takes a complex, difficult subject and makes it fun, interesting, and relevant.”
—Peter Orszag, former director of the Office of Management and Budget
“Projection, prediction, assumption, trepidation, anticipation, expectation, estimation… we wouldn’t have 80 words like this in the English language if it wasn’t central to our lives. We tend not to take prediction seriously because, on some level, we know that we don’t know. Silver shows us how this inevitable part of life goes awry when projected on a grand scale into the murky worlds of politics, science and economics. Dancing through chess, sports, snowstorms, global warming and the McLaughlin Group, he makes a serious and systematic effort to show us how to clean the noise off the signal.”
—Bill James, author of The Bill James Baseball Abstracts
Most helpful customer reviews
752 of 785 people found the following review helpful.
Much-needed insight to understand and improve predictive science
By Sitting in Seattle
This is the best general-readership book on applied statistics that I've read. Short review: if you're interested in science, economics, or prediction: read it. It's full of interesting cases, builds intuition, and is a readable example of Bayesian thinking.
Longer review: I'm an applied business researcher and that means my job is to deliver quality forecasts: to make them, persuade people of them, and live by the results they bring. Silver's new book offers a wealth of insight for many different audiences. It will help you to develop intuition for the kinds of predictions that are possible, that are not so possible, where they may go wrong, and how to avoid some common pitfalls.
The core concept is this: prediction is a vital part of science, of business, of politics, of pretty much everything we do. But we're not very good at it, and fall prey to cognitive biases and other systemic problems such as information overload that make things worse. However, we are simultaneously learning more about how such things occur and that knowledge can be used to make predictions better -- and to improve our models in science, politics, business, medicine, and so many other areas.
The book presents real-world experience and critical reflection on what happens to research in social contexts. Data-driven models with inadequate theory can lead to terrible inferences. For example, on p. 162: "What happens in systems with noisy data and underdeveloped theory - like earthquake prediction and parts of economic and political science - is a two-step process. First, people start to mistake the noise for a signal. Second, this noise pollutes journals, blogs, and news accounts with false alarms, undermining good science and setting back our ability to understand how the system really works." This is the kind of insight that every good practitioner acquires through hard-won battles, and continues to wrestle every day both in doing work and in communicating it to others.
It is both readable and technically accurate: it presents just enough model details yet avoids being formula-heavy. Statisticians will be able to reproduce models similar to the ones he discusses, but general readers will not be left out: the material is clear and applicable. Scholars of all stripes will appreciate the copious notes and citations, 56 pages of notes and another 20 pages of index, which detail the many sources. It is also important to note that this is perhaps the best general readership book from a Bayesian perspective -- a viewpoint that is overdue for readable exposition.
The models cover a diversity of areas from baseball to politics, from earthquakes to finance, from climate science to chess. Of course this makes the book fascinating to generalists, geeks, and breadth thinkers, but perhaps more importantly, I think it serves well to develop reusable intuition across domains. And, for those of us who practice such things professionally, to bring stories and examples that we can tell and use to illustrate concepts with the people we inform.
There are three audiences who might not appreciate the book as much. First are students looking for a how-to book. Silver provides a lot of pointers and examples, but does not get into nuts and bolts details or supply foundational technical instruction. That requires coursework in research methods and and statistics. Second, his approach to doing multiple models and interpreting them humbly will not satisfy those who promote a naive, gee-whiz, "look how great these new methods are" approach to research. But then, that's not a problem; it's a good thing. The third non-fitting audience will be experts who desire depth in one of the book's many topic areas; it's not a technical treatise for them and I can confidently predict grumbling in some quarters. Overall, those three audiences are small, which happily leaves the rest of us to enjoy the book.
What would make it better? As a pro, I'd like a little more depth (of course). It emphasizes games a little too much for my taste. And a clearer prescriptive framework could be nice (but also could be a problem for reasons he illustrates). But those are minor points; it hits its target better than any other such book I know.
Conclusion: if you're interested in scientific or statistical forecasting, either as a professional or layperson, or if you simply enjoy general science books, get it. Cheers!
296 of 310 people found the following review helpful.
Great book, and here are some takeaways
By Kindle Customer
Excellent book!!! People looking for a "how to predict" silver bullet will (like some reviewers here) be disappointed, mainly because Silver is too honest to pretend that such a thing exists. The anecdotes and exposition are fantastic, and I wish we could make this book required reading for, say, everyone in the country.
During election season, everyone with a newspaper column or TV show feels entitled to make (transparently partisan) predictions about the consequences of each candidate's election to unemployment/crime/abortion/etc. This kind of pundit chatter, as Silver notes, tends to be insanely inaccurate. But there are also some amazing success stories in the prediction business. I list some chapter-by-chapter takeaways below (though there's obviously a lot depth more to the book than I can fit into a list like this):
1. People have puzzled over prediction and uncertainty for centuries.
2. TV pundits make terrible predictions, no better than random guesses. They are rewarded for being entertaining, and not really penalized for being wrong.
3. Statistics has revolutionized baseball. But computer geeks have not replaced talent scouts altogether. They're working together in more interesting ways now.
4. Weather prediction has gotten lots better over the last fifty years, due to highly sophisticated, large-scale supercomputer modeling.
5. We have almost no ability to predict earthquakes. But we know that some regions are more earthquake prone, and that in a given region an earthquake of magnitude n happens about ten times as often as an earthquake of magnitude (n+1).
6. Economists are terrible at predicting quantities such as next year's GDP. Predictions are only very slightly correlated with reality. They also tend to be overconfident, drastically underestimating the margin of error in their guesses. Politically motivated predictions (such as those released by White House, historically) are even worse.
7. The spread of a disease like the flu is hard to predict. Sometimes we overreact because risk of under-reacting seems greater.
8. A few professional sports gamblers are able to make make a living by spotting meaningful patterns before others do, and being right slightly more than half the time.
9. Kasparov thought he could beat Deep Blue. Couldn't. Interesting tale of humans/computers trying to outguess each other.
10. Nate Silver made a living playing online poker for a few years. When the government tightened the rules, the less savvy players ("fish") stopped playing, and he found he couldn't make money any more. So he started FiveThirtyEight.
11. Efficient market hypothesis: market seems very efficient, but not perfectly so. Possible source of error: most investment is done by institutions, and individuals at these institutions are rewarded based on short term profits. Rational employees may have less career risk when they "bet with the consensus" than when they buck a trend: this may increase herding effects and makes bubbles worse. Note: Nate pointedly does not claim that one can make money on Intrade by betting based on FiveThirtyEight probabilities. But he stresses that Intrade prices are themselves probably heavily informed by poll-based models like the ones on FiveThirtyEight.
12. Climate prediction: prima facie case for anthropic warming is very strong (greenhouse gas up, temperature up, good theoretical reason for former causing latter). But lots of good reason to doubt accuracy of specific elaborate computer models, and most scientists admit uncertainty about details.
13. We failed to predict both Pearl Harbor and September 11. Unknown unknowns got us. Got to watch out for loose Pakistani nukes and other potential catastrophic surprises in the future.
1 of 1 people found the following review helpful.
I liked this book, but, then again, I am a geek.
By RonnieT
Nate Silver is best known for using polling data to call political elections. He missed on the Trump win, but was pretty good up until then.
The Signal and the Noise is a well written, well researched and well reasoned book about forecasting and the various mistakes that prognosticators make. He addresses failures as the inability of economists and others to foresee the bursting of the housing bubble and the chaos it created in 2008. Other themes include easier-to-predict subjects such as future performance of major league baseball players and the success (or not) of poker players. In these later two, he has real world experience as he developed software to predict baseball player performance and made a living as a professional poker player.
Other forecasting areas that he writes about include weather (a modern success); earthquakes (not so much due to difficulties in differentiating the signal from the noise); the spread of infectious diseases (difficult to model due to human behaviour); and climate change (right on warming but uncertain about effects).
One of the over all themes involves the Bayes Theorem. This requires an a priori hunch about the chances of an event that is refined by future observations and experimenting.
There were sections I like more than others, but this may correlate more with my affinity for the subjects rather than Silver's reporting. I particularly like the section on Climate Change research. It was thoughtful and open-minded. As he does throughout the book, he looks at the facts and the stats and interviews the people involved in the research.
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