The Signal and the Noise: Why So Many Predictions Fail--but Some Don't

The Signal and the Noise: Why So Many Predictions Fail--but Some Don't

by Nate Silver
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The Signal and the Noise: Why So Many Predictions Fail--but Some Don't by Nate Silver

One of Wall Street Journal's Best Ten Works of Nonfiction in 2012
New York Times Bestseller

“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
"Nate Silver's The Signal and the Noise is The Soul of a New Machine for the 21st century."
—Rachel Maddow, author of Drift

"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

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 the website FiveThirtyEight. 
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.

Product Details

ISBN-13: 9780143125082
Publisher: Penguin Publishing Group
Publication date: 02/03/2015
Pages: 560
Sales rank: 61,024
Product dimensions: 5.40(w) x 8.40(h) x 1.30(d)
Age Range: 18 Years

About the Author

Nate Silver is the founder and editor in chief of

Read an Excerpt

At about the time The Signal and the Noise was first published in September 2012, “Big Data” was on its way becoming a Big Idea. Google searches for the term doubled over the course of a year,1 as did mentions of it in the news media.2 Hundreds of books were published on the subject. If you picked up any business periodical in 2013, advertisements for Big Data were as ubiquitous as cigarettes in an episode of Mad Men.
But by late 2014, there was evidence that trend had reached its apex. The frequency with which Big Data was mentioned in corporate press releases had slowed down and possibly begun to decline.3 The technology research firm Gartner even declared that Big Data had passed the peak of its “hype cycle.”4
I hope that Gartner is right. Coming to a better understanding of data and statistics is essential to help us navigate our lives. But as with most emerging technologies, the widespread benefits to science, industry, and human welfare will come only after the hype has died down.
I worry that certain events in my life have contributed to the hype cycle. On November 6, 2012, the statistical model at my Web site FiveThirtyEight “called” the winner of the American presidential election correctly in all fifty states. I received a congratulatory phone call from the White House. I was hailed as “lord and god of the algorithm” by The Daily Show’s Jon Stewart. My name briefly received more Google search traffic than the vice president of the United States.
I enjoyed some of the attention, but I felt like an outlier—even a fluke. Mostly I was getting credit for having pointed out the obvious—and most of the rest was luck.*
To be sure, it was reasonably clear by Election Day that President Obama was poised to win reelection. When voters went to the polls on election morning, FiveThirtyEight’s statistical model put his chances of winning the Electoral College at about 90 percent.* A 90 percent chance is not quite a sure thing: Would you board a plane if the pilot told you it had a 90 percent chance of landing successfully? But when there’s only reputation rather than life or limb on the line, it’s a good bet. Obama needed to win only a handful of the swing states where he was tied or ahead in the polls; Mitt Romney would have had to win almost all of them.
But getting every state right was a stroke of luck. In our Election Day forecast, Obama’s chance of winning Florida was just 50.3 percent—the outcome was as random as a coin flip. Considering other states like Virginia, Ohio, Colorado, and North Carolina, our chances of going fifty-for-fifty were only about 20 percent.5 FiveThirtyEight’s “perfect” forecast was fortuitous but contributed to the perception that statisticians are soothsayers—only using computers rather than crystal balls.
This is a wrongheaded and rather dangerous idea. American presidential elections are the exception to the rule—one of the few examples of a complex system in which outcomes are usually more certain than the conventional wisdom implies. (There are a number of reasons for this, not least that the conventional wisdom is often not very wise when it comes to politics.) Far more often, as this book will explain, we overrate our ability to predict the world around us. With some regularity, events that are said to be certain fail to come to fruition—or those that are deemed impossible turn out to occur.
If all of this is so simple, why did so many pundits get the 2012 election wrong? It wasn’t just on the fringe of the blogosphere that conservatives insisted that the polls were “skewed” toward President Obama. Thoughtful conservatives like George F. Will6 and Michael Barone7 also predicted a Romney win, sometimes by near-landslide proportions.
One part of the answer is obvious: the pundits didn’t have much incentive to make the right call. You can get invited back on television with a far worse track record than Barone’s or Will’s—provided you speak with some conviction and have a viewpoint that matches the producer’s goals.
An alternative interpretation is slightly less cynical but potentially harder to swallow: human judgment is intrinsically fallible. It’s hard for any of us (myself included) to recognize how much our relatively narrow range of experience can color our interpretation of the evidence. There’s so much information out there today that none of us can plausibly consume all of it. We’re constantly making decisions about what Web site to read, which television channel to watch, and where to focus our attention.
Having a better understanding of statistics almost certainly helps. Over the past decade, the number of people employed as statisticians in the United States has increased by 35 percent8 even as the overall job market has stagnated. But it’s a necessary rather than sufficient part of the solution. Some of the examples of failed predictions in this book concern people with exceptional intelligence and exemplary statistical training—but whose biases still got in the way.
These problems are not so simple and so this book does not promote simple answers to them. It makes some recommendations but they are philosophical as much as technical. Once we’re getting the big stuff right—coming to a better understanding of probably and uncertainty; learning to recognize our biases; appreciating the value of diversity, incentives, and experimentation—we’ll have the luxury of worrying about the finer points of technique.
Gartner’s hype cycle ultimately has a happy ending. After the peak of inflated expectations there’s a “trough of disillusionment”—what happens when people come to recognize that the new technology will still require a lot of hard work.
But right when views of the new technology have begun to lapse from healthy skepticism into overt cynicism, that technology can begin to pay some dividends. (We’ve been through this before: after the computer boom in the 1970s and the Internet commerce boom of the late 1990s, among other examples.) Eventually it matures to the point when there are fewer glossy advertisements but more gains in productivity—it may even have become so commonplace that we take it for granted. I hope this book can accelerate the process, however slightly.
This is a book about information, technology, and scientific progress. This is a book about competition, free markets, and the evolution of ideas. This is a book about the things that make us smarter than any computer, and a book about human error. This is a book about how we learn, one step at a time, to come to knowledge of the objective world, and why we sometimes take a step back.
This is a book about prediction, which sits at the intersection of all these things. It is a study of why some predictions succeed and why some fail. My hope is that we might gain a little more insight into planning our futures and become a little less likely to repeat our mistakes.
More Information, More Problems
The original revolution in information technology came not with the microchip, but with the printing press. Johannes Gutenberg’s invention in 1440 made information available to the masses, and the explosion of ideas it produced had unintended consequences and unpredictable effects. It was a spark for the Industrial Revolution in 1775,1 a tipping point in which civilization suddenly went from having made almost no scientific or economic progress for most of its existence to the exponential rates of growth and change that are familiar to us today. It set in motion the events that would produce the European Enlightenment and the founding of the American Republic.
But the printing press would first produce something else: hundreds of years of holy war. As mankind came to believe it could predict its fate and choose its destiny, the bloodiest epoch in human history followed.2
Books had existed prior to Gutenberg, but they were not widely written and they were not widely read. Instead, they were luxury items for the nobility, produced one copy at a time by scribes.3 The going rate for reproducing a single manuscript was about one florin (a gold coin worth about $200 in today’s dollars) per five pages,4 so a book like the one you’re reading now would cost around $20,000. It would probably also come with a litany of transcription errors, since it would be a copy of a copy of a copy, the mistakes having multiplied and mutated through each generation.
This made the accumulation of knowledge extremely difficult. It required heroic effort to prevent the volume of recorded knowledge from actually decreasing, since the books might decay faster than they could be reproduced. Various editions of the Bible survived, along with a small number of canonical texts, like from Plato and Aristotle. But an untold amount of wisdom was lost to the ages,5 and there was little incentive to record more of it to the page.
The pursuit of knowledge seemed inherently futile, if not altogether vain. If today we feel a sense of impermanence because things are changing so rapidly, impermanence was a far more literal concern for the generations before us. There was “nothing new under the sun,” as the beautiful Bible verses in Ecclesiastes put it—not so much because everything had been discovered but because everything would be forgotten.6
The printing press changed that, and did so permanently and profoundly. Almost overnight, the cost of producing a book decreased by about three hundred times,7 so a book that might have cost $20,000 in today’s dollars instead cost $70. Printing presses spread very rapidly throughout Europe; from Gutenberg’s Germany to Rome, Seville, Paris, and Basel by 1470, and then to almost all other major European cities within another ten years.8 The number of books being produced grew exponentially, increasing by about thirty times in the first century after the printing press was invented.9 The store of human knowledge had begun to accumulate, and rapidly.
As was the case during the early days of the World Wide Web, however, the quality of the information was highly varied. While the printing press paid almost immediate dividends in the production of higher quality maps,10 the bestseller list soon came to be dominated by heretical religious texts and pseudoscientific ones.11 Errors could now be mass-produced, like in the so-called Wicked Bible, which committed the most unfortunate typo in history to the page: thou shalt commit adultery.12 Meanwhile, exposure to so many new ideas was producing mass confusion. The amount of information was increasing much more rapidly than our understanding of what to do with it, or our ability to differentiate the useful information from the mistruths.13 Paradoxically, the result of having so much more shared knowledge was increasing isolation along national and religious lines. The instinctual shortcut that we take when we have “too much information” is to engage with it selectively, picking out the parts we like and ignoring the remainder, making allies with those who have made the same choices and enemies of the rest.
The most enthusiastic early customers of the printing press were those who used it to evangelize. Martin Luther’s Ninety-five Theses were not that radical; similar sentiments had been debated many times over. What was revolutionary, as Elizabeth Eisenstein writes, is that Luther’s theses “did not stay tacked to the church door.”14 Instead, they were reproduced at least three hundred thousand times by Gutenberg’s printing press15—a runaway hit even by modern standards.
The schism that Luther’s Protestant Reformation produced soon plunged Europe into war. From 1524 to 1648, there was the German Peasants’ War, the Schmalkaldic War, the Eighty Years’ War, the Thirty Years’ War, the French Wars of Religion, the Irish Confederate Wars, the Scottish Civil War, and the English Civil War—many of them raging simultaneously. This is not to neglect the Spanish Inquisition, which began in 1480, or the War of the Holy League from 1508 to 1516, although those had less to do with the spread of Protestantism. The Thirty Years’ War alone killed one-third of Germany’s population,16 and the seventeenth century was possibly the bloodiest ever, with the early twentieth staking the main rival claim.17
But somehow in the midst of this, the printing press was starting to produce scientific and literary progress. Galileo was sharing his (censored) ideas, and Shakespeare was producing his plays.
Shakespeare’s plays often turn on the idea of fate, as much drama does. What makes them so tragic is the gap between what his characters might like to accomplish and what fate provides to them. The idea of controlling one’s fate seemed to have become part of the human consciousness by Shakespeare’s time—but not yet the competencies to achieve that end. Instead, those who tested fate usually wound up dead.18
These themes are explored most vividly in The Tragedy of Julius Caesar. Throughout the first half of the play Caesar receives all sorts of apparent warning signs—what he calls predictions19 (“beware the ides of March”)—that his coronation could turn into a slaughter. Caesar of course ignores these signs, quite proudly insisting that they point to someone else’s death—or otherwise reading the evidence selectively. Then Caesar is assassinated.
“[But] men may construe things after their fashion / Clean from the purpose of the things themselves,” Shakespeare warns us through the voice of Cicero—good advice for anyone seeking to pluck through their newfound wealth of information. It was hard to tell the signal from the noise. The story the data tells us is often the one we’d like to hear, and we usually make sure that it has a happy ending.
And yet if The Tragedy of Julius Caesar turned on an ancient idea of prediction—associating it with fatalism, fortune-telling, and superstition—it also introduced a more modern and altogether more radical idea: that we might interpret these signs so as to gain an advantage from them. “Men at some time are masters of their fates,” says Cassius, hoping to persuade Brutus to partake in the conspiracy against Caesar.
The idea of man as master of his fate was gaining currency. The words predict and forecast are largely used interchangeably today, but in Shakespeare’s time, they meant different things. A prediction was what the soothsayer told you; a forecast was something more like Cassius’s idea.
The term forecast came from English’s Germanic roots,20 unlike predict, which is from Latin.21 Forecasting reflected the new Protestant worldliness rather than the otherworldliness of the Holy Roman Empire. Making a forecast typically implied planning under conditions of uncertaintyIt suggested having prudence, wisdom, and industriousness, more like the way we now use the word foresight. 22
The theological implications of this idea are complicated.23 But they were less so for those hoping to make a gainful existence in the terrestrial world. These qualities were strongly associated with the Protestant work ethic, which Max Weber saw as bringing about capitalism and the Industrial Revolution.24 This notion of forecasting was very much tied in to the notion of progress. All that information in all those books ought to have helped us to plan our lives and profitably predict the world’s course.
•   •   •
The Protestants who ushered in centuries of holy war were learning how to use their accumulated knowledge to change society. The Industrial Revolution largely began in Protestant countries and largely in those with a free press, where both religious and scientific ideas could flow without fear of censorship.25
The importance of the Industrial Revolution is hard to overstate. Throughout essentially all of human history, economic growth had proceeded at a rate of perhaps 0.1 percent per year, enough to allow for a very gradual increase in population, but not any growth in per capita living standards.26 And then, suddenly, there was progress when there had been none. Economic growth began to zoom upward much faster than the growth rate of the population, as it has continued to do through to the present day, the occasional global financial meltdown notwithstanding.27

Table of Contents

Preface to the Paperback Edition xiii

Introduction 1

1 A Catastrophic Failure of Prediction 19

2 Are You Smarter Than a Television Pundit? 47

3 All I Care About Is W's and Ls 74

4 For Years You've Been Telling Us That Rain Is Green 108

5 Desperately Seeking Signal 142

6 How to Drown in Three Feet of Water 176

7 Role Models 204

8 Less and Less and Less Wrong 232

9 Rage Against the Machines 262

10 The Poker Bubble 294

11 If You Can't Beat'em … 329

12 A Climate of Healthy Skepticism 370

13 What you Don't Know Can Hurt You 412

Conclusion 446

Acknowledgments 455

Notes 459

Index 517

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The Signal and the Noise: Why So Many Predictions Fail but Some Don't 3.8 out of 5 based on 0 ratings. 42 reviews.
popscipopulizer More than 1 year ago
*A full executive summary of this book will be available at newbooksinbrief . wordpress . com, on or before Monday, October 15, 2012. Making decisions based on an assessment of future outcomes is a natural and inescapable part of the human condition. Indeed, as Nate Silver points out, "prediction is indispensable to our lives. Every time we choose a route to work, decide whether to go on a second date, or set money aside for a rainy day, we are making a forecast about how the future will proceed--and how our plans will affect the odds for a favorable outcome" (loc. 285). And over and above these private decisions, prognosticating does, of course, bleed over into the public realm; as indeed whole industries from weather forecasting, to sports betting, to financial investing are built on the premise that predictions of future outcomes are not only possible, but can be made reliable. As Silver points out, though, there is a wide discrepancy across industries and also between individuals regarding just how accurate these predictions are. In his new book `The Signal and the Noise: Why So Many Predictions Fail--but Some Don't' Silver attempts to get to the bottom of all of this prediction-making to uncover what separates the accurate from the misguided. In doing so, the author first takes us on a journey through financial crashes, political elections, baseball games, weather reports, earthquakes, disease epidemics, sports bets, chess matches, poker tables, and the good ol' American economy, as we explore what goes into a well-made prediction and its opposite. The key teaching of this journey is that wise predictions come out of self-awareness, humility, and attention to detail: lack of self-awareness causes us to make predictions that tell us what we'd like to hear, rather than what is true (or most likely the case); lack of humility causes us to feel more certain than is warranted, leading us to rash decisions; and lack of attention to detail (in conjunction with self-serving bias and rashness) leads us to miss the key variables that make all the difference. Attention to detail is what we need to capture the signal in the noise (the key variable[s] in the sea of data and information that are integral in determining future outcomes), but without self-awareness and humility, we don't even stand a chance. In the final stage of the book Silver explores how the lessons that he lays out can be applied to such issues as global warming, terrorism and bubbles in financial markets. Unfortunately, each of these fields is a lot noisier than many of us would like to think (thus making them very difficult to predict precisely). Nevertheless, the author argues, within each there are certain signals that can help us make better predictions regarding them, and which should help make the world a safer and more livable place. If you are hoping that this book will make you a fool-proof prognosticator, you are going to be disappointed. A key tenet of the book is that this is simply not possible (no matter what field you are in). That being said, Silver makes a very strong argument that by applying a few simple principles (and putting in a lot of hard work in identifying key variables) our predictive powers should take a great boost indeed. A full executive summary of this book will be available at newbooksinbrief . wordpress . com, on or before Monday, October 15; a podcast discussion of the book will be available shortly thereafter.
ProfJane More than 1 year ago
I teach probability and statistics and really wanted to like this book, but Nate Silver is NOT on expert on statistics and probability and makes some pretty big errors as a consequence. Chapter 8 completely fails in its explanation of the controversy between classical and Bayesian methods. In other chapters, Silver seems to believe that anyone who revises his/her beliefs based on new information is using Bayes's theorem. Bayes's theorem involves reasoning based on how likely the information is if the hypothesis is true versus how likely the information is if the hypothesis is false.
Anonymous More than 1 year ago
Silver draws on a wide range of activities with examples from poker, sports, finance, etc. that involve his own experiences and interviews with others. His goal is to uncover significant principles and factors and not to expound a specific theory. The book is well organized and easy to read.
BrandonSams More than 1 year ago
This book is about statistical analysis, and what role that plays in our lives. Nate Silver is a perfect person to write a book on this subject, as he has gotten famous for not only understanding the rock hard quantitative analysis that underlies the field, but being able to explain it to a more general audience. This is the approach that he sticks to with this book. He will often present a very big theoretical claim, which is difficult to grapple with, as some of the statistical analysis is non-intuitive. Silver will then proceed to make analogies in order to make the idea more approachable. This seems like a fair approach, but it will often force the reader to re-read the same section over and over again to understand the big theory itself. This is one of the major downfalls to the book as a whole. I, as a reader, would prefer to have this process reversed, where a basic approachable example would be presented, and then the theory is presented to explain this phenomenon. The chapter structure of the book was a mix of good and bad. The good: the first half of the book talked about statistical analysis and what made it effective/ineffective. The second part of the book was centered around Bayesian thinking and calculation as a method to improve the statistical models presented in the first half. THIS WAS A VERY EFFECTIVE APPROACH. However, the order of the chapters in each of the halves was very odd. The book began by talking about the financial crisis, which was COMPLETELY incoherent to a person like me who does not have an economic background. The chapters gradually got more approachable by way of subject matter as the book progressed. This process was once again, backwards in my opinion. I was very tempted to stop reading during the first chapter, but I pressed on. This book feels like it was reverse engineered, which is fine, but can alienate a good portion of its readers. As far as writing style, the ideas were never unclear because of writing, but because of content. (Statistics is hard). I find this very impressive, and would recommend this book to anybody looking to learn about statistics. It does draw on some truly impressive ideas, which are a joy to have access to now that I have read the book. I recommend it to anyone looking to learn more about prediction and forecasting, but read it with a grain of salt. It can be confusing at times, but the book is excellent.
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I enjoyed reading this book and the author's efforts to sort out all the predictions that we encounter in daily life.  I needed to learn to put down the book after finishing a chapter so that I could absorb the points being made. Wish that the book would have been around when I was taking statistics.  Certainly he gave a lot of encouragement to thinking about probabilities rather than just doing counts.
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Georgia_writer More than 1 year ago
A very well-written and fascinating presentation on why some predictions work and many others fail. If you're at all interested in politics, economics, disease spread, terrorism, the stock market, weather, earthquakes, baseball, chess or poker you'll be captivated by The Signal and the Noise. I'm primarily a fiction reader, but found this book to be as much or more of a page turner than many "thrillers." Although the book is written for the layman, you'll have an easier time with it if you have a solid grounding in fundamental mathematics and statistics. Bottom line: if you're curious about the world we live in and why some events are easier to predict than others, I highly recommend this book.
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BeeMD More than 1 year ago
I was inspired to do some research on Bayes' theorem after finishing the text. Footnotes and references make up a large part of the book, but are gathered at the end, not within the text.
Anonymous More than 1 year ago
Anonymous More than 1 year ago
Nate Silver, has taken time out to write an eye opening book. Before reading this book I had taken prediction for granted, but after reading it, I have come to appreciate the effort that goes into prediction and also how we are surrounded with predictions. It has also helped improve my prediction ability, because those that predict rightly, controls the future and ultimately wins in the long run.
Excusemesir More than 1 year ago
I finished reading "The Signal and the Noise" a couple of weeks ago, and although I enjoyed it as I read it, I find that it is already fading into the background of other related books that I have read. Occasionally I come across a book that requires re-reading and pondering, but this is not one of them. On the other hand, if you are new to this discussion, Mr. Silver does a good job of organizing and summarizing the problems with making accurate and reliable predictions. My summary of the book (and of the field of predicting the future): Predict that tomorrow will be pretty much like today, and you will have a very high accuracy rate, but you'll be BOOOOORRRIIINNNGG. Predict great and dramatic changes, and you will usually miss, but if you do it in an authoritative and entertaining fashion, you'll get lots of attention anyway.
Anonymous More than 1 year ago
Some very interesting and useful concepts are explained. In particular the usefulness of Bayes Theorum for refining predictions is clearly set forth. The book needs editing. The same ground seems to be covered over and over. If you are short of time you could read just those chapters that deal with an area of your interest: gambling, weather, epidemics, or terrorism. I predict that 20% of those who start the book will not finish it.
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