Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists [NOOK Book]


Here, by popular demand, is the updated edition to Joel Best's classic guide to understanding how numbers can confuse us. In his new afterword, Best uses examples from recent policy debates to reflect on the challenges to improving statistical literacy. Since its publication ten years ago, Damned Lies and Statistics has emerged as the go-to handbook for spotting bad statistics and learning to think critically about these influential numbers.
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Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists

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Here, by popular demand, is the updated edition to Joel Best's classic guide to understanding how numbers can confuse us. In his new afterword, Best uses examples from recent policy debates to reflect on the challenges to improving statistical literacy. Since its publication ten years ago, Damned Lies and Statistics has emerged as the go-to handbook for spotting bad statistics and learning to think critically about these influential numbers.
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Editorial Reviews

San Diego Union-Tribune
There's a 73 percent chance that the University of Delaware prof has got our number.
Washington Times
Damned Lies and Statistics is highly entertaining as well as instructive. Best's book shows how some of those big numbers indicating big social problems were created in the first place and instructs the reader (and reporter how to be on guard against such gross manipulation. And it doesn't take an understanding of advanced mathematics to do so thanks to this book, which ought to be required reading in every newsroom in the country.
Whether we like them or not, we have to live with statistics, and Damned Lies and Statistics offers a useful guide for engaging with their troublesome world. Despite the temptation to be cynical, the author of this timely and excellent work cautions the reader against reacting in such a way to statistics. What we are offered is an approach that helps us to work out the real story behind those numbers.
Boston Globe
Deserves a place next to the dictionary on every school, media, and home-office desk.
Christian Science Monitor
A clearly written primer for the statistically impaired. It is as important to discussions of public policy as any book circulating today.
New Scientist
Definitely a must for politicians, activists and others who generate or use statistics, but especially for those who want to think for themselves rather than take as gospel every statistic presented to them.
The narrative flows easily, and all the points are driven home with engaging examples from real life. I found Best's book a delight. Always engaging, it is accessible to a lay reader, yet will reward the expert; the examples it gives could enrich both a primary schoolroom and a university lecture hall.
Patricia Adler
Best is at it again! In Damned Lies and Statistics he shows how statistics are manipulated, mismanaged, misrepresented, and massaged by officials and other powerful groups to promote their agendas. He is a master at examining taken-for-granted facts and debunking them through careful sociological scrutiny.
author of Peer Power
Publishers Weekly - Publisher's Weekly
Who really said, "There are lies, damned lies, and statistics" Mark Twain or Benjamin Disraeli? Best, professor of sociology at the University of Delaware and author of several books, including Random Violence, settles the question once and for all: Disraeli (whom Twain credits for his use of the remark in his autobiography). The quote's misattribution is similar to the twisted course statistics often take as they "mutate" into bar-chart monsters with slim if any relation to the original numbers or reality. For instance, a few years ago it was estimated that 150,000 American women are anorexic. Somehow, this mutated into an erroneous if not dangerous statistic: 150,000 women die annually from anorexia. Since only about 55,500 American women between 15 and 44 (the age range for most cases of anorexia) die from all causes each year, this number challenges common sense and the ability of reporters to question what they write about. But it has become a frequently cited, "authoritative" figure that's hard to dispute. Best explains in untechnical language important statistical concepts like "dark figures," "false positives" and "false negatives," and how statisticians often err in comparing dissimilar groups (e.g., test scores of American high school students to those of Europeans, with their multitrack systems of secondary education). He has an annoying habit of italicizing words and phrases to emphasize a point, and he conflates "activists" and "advocates" (academic writers' favorite bogeymen as purveyors of suspect statistics), but these are minor issues. This informative and well-written little book will be a particularly worthwhile addition to libraries' collections and will help all readers become savvier and more critical news consumers. (May) Copyright 2001 Cahners Business Information.
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Product Details

  • ISBN-13: 9780520953512
  • Publisher: University of California Press
  • Publication date: 8/7/2012
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • Pages: 224
  • Sales rank: 353,134
  • File size: 244 KB

Meet the Author

Joel Best is Professor of Sociology and Criminal Justice at the University of Delaware. His many books include Everyone’s A Winner: Life in Our Congratulatory Culture and Stat-Spotting: A Field Guide to Dubious Data, both from UC Press.
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Read an Excerpt

Chapter One


Nineteenth-century Americans worried about prostitution; reformers called it "the social evil" and warned that many women prostituted themselves. How many? For New York City alone, there were dozens of estimates: in 1833, for instance, reformers published a report declaring that there were "not less than 10,000" prostitutes in New York (equivalent to about 10 percent of the city's female population); in 1866, New York's Methodist bishop claimed there were more prostitutes (11,000 to 12,000) than Methodists in the city; other estimates for the period ranged as high as 50,000. These reformers hoped that their reports of widespread prostitution would prod the authorities to act, but city officials' most common response was to challenge the reformers' numbers. Various investigations by the police and grand juries produced their own, much lower estimates; for instance, one 1872 police report counted only 1,223 prostitutes (by that time, New York's population included nearly half a million females). Historians see a clear pattern in these cycles of competing statistics: ministers and reformers "tended to inflate statistics"; while "police officials tended to underestimate prostitution."

    Antiprostitution reformers tried to use big numbers to arouse public outrage. Big numbers meant there was a big problem: if New York had tens of thousands of prostitutes, something ought to be done. In response, the police countered that there were relatively few prostitutes—an indication that they were doing a goodjob. These dueling statistics resemble other, more recent debates. During Ronald Reagan's presidency, for example, activists claimed that three million Americans were homeless, while the Reagan administration insisted that the actual number of homeless people was closer to 300,000, one-tenth what the activists claimed. In other words, homeless activists argued that homelessness was a big problem that demanded additional government social programs, while the administration argued new programs were not needed to deal with what was actually a much smaller, more manageable problem. Each side presented statistics that justified its policy recommendations, and each criticized the other's numbers. The activists ridiculed the administration's figures as an attempt to cover up a large, visible problem, while the administration insisted that the activists' numbers were unrealistic exaggerations.

    Statistics, then, can become weapons in political struggles over social problems and social policy. Advocates of different positions use numbers to make their points ("It's a big problem!" "No, it's not!"). And, as the example of nineteenth-century estimates of prostitution reminds us, statistics have been used as weapons for some time.


In fact, the first "statistics" were meant to influence debates over social issues. The term acquired its modern meaning—numeric evidence—in the 1830s, around the time that New York reformers estimated that the city had 10,000 prostitutes. The forerunner of statistics was called "political arithmetic"; these studies—mostly attempts to calculate population size and life expectancy—emerged in seventeenth-century Europe, particularly in England and France. Analysts tried to count births, deaths, and marriages because they believed that a growing population was evidence of a healthy state; those who conducted such numeric studies—as well as other, nonquantitative analyses of social and political prosperity—came to be called statists. Over time, the statists' social research led to the new term for quantitative evidence: statistics.

    Early social researchers believed that information about society could help governments devise wise policies. They were well aware of the scientific developments of their day and, like other scientists, they came to value accuracy and objectivity. Counting—quantifying—offered a way of making their studies more precise, and let them concisely summarize lots of information. Over time, social research became less theoretical and more quantitative. As the researchers collected and analyzed their data, they began to see patterns. From year to year, they discovered, the numbers of births, deaths, and even marriages remained relatively stable; this stability suggested that social arrangements bad an underlying order, that what happened in a society depended on more than simply its government's recent actions, and analysts began paying more attention to underlying social conditions.

    By the beginning of the nineteenth century, the social order seemed especially threatened: cities were larger than ever before; economies were beginning to industrialize; and revolutions in America and France had made it clear that political stability could not be taken for granted. The need for information, for facts that could guide social policy, was greater than ever before. A variety of government agencies began collecting and publishing statistics: the United States and several European countries began conducting regular censuses to collect population statistics; courts, prisons, and police began keeping track of the numbers of crimes and criminals; physicians kept records of patients; educators counted students; and so on. Scholars organized statistical societies to share the results of their studies and to discuss the best methods for gathering and interpreting statistics. And reformers who sought to confront the nineteenth-century's many social problems—the impoverished and the diseased, the fallen woman and the child laborer, the factory workforce and dispossessed agricultural labor—found statistics useful in demonstrating the extent and severity of suffering. Statistics gave both government officials and reformers hard evidence—proof that what they said was true. Numbers offered a kind of precision: instead of talking about prostitution as a vaguely defined problem, reformers began to make specific, numeric claims (for example, that New York had 10,000 prostitutes).

    During the nineteenth century, then, statistics—numeric statements about social life—became an authoritative way to describe social problems. There was growing respect for science, and statistics offered a way to bring the authority of science to debates about social policy. In fact, this had been the main goal of the first statisticians—they wanted to study society through counting and use the resulting numbers to influence social policy. They succeeded; statistics gained widespread acceptance as the best way to measure social problems. Today, statistics continue to play a central role in our efforts to understand these problems. But, beginning in the nineteenth century and continuing through today, social statistics have had two purposes, one public, the other often hidden. Their public purpose is to give an accurate, true description of society. But people also use statistics to support particular views about social problems. Numbers are created and repeated because they supply ammunition for political struggles, and this political purpose is often hidden behind assertions that numbers, simply because they are numbers, must be correct. People use statistics to support particular points of view, and it is naive simply to accept numbers as accurate, without examining who is using them and why.


We tend to think of social problems as harsh realities, like gravity or earthquakes, that exist completely independent of human action. But the very term reveals that this is incorrect: social problems are products of what people do.

    This is true in two senses. First, we picture social problems as snarls or flaws in the social fabric. Social problems have their causes in society's arrangements; when some women turn to prostitution or some individuals have no homes, we assume that society has failed (although we may disagree over whether that failure involves not providing enough jobs, or not giving children proper moral instruction, or something else). Most people understand that social problems are social in this sense.

    But there is a second reason social problems are social. Someone has to bring these problems to our attention, to give them names, describe their causes and characteristics, and so on. Sociologists speak of social problems being "constructed"—that is, created or assembled through the actions of activists, officials, the news media, and other people who draw attention to particular problems. "Social problem" is a label we give to some social conditions, and it is that label that turns a condition we take for granted into something we consider troubling. This means that the processes of identifying and publicizing social problems are important. When we start thinking of prostitution or homelessness as a social problem, we are responding to campaigns by reformers who seek to arouse our concern about the issue.

    The creation of a new social problem can be seen as a sort of public drama, a play featuring a fairly standard cast of characters. Often, the leading roles are played by social activists—individuals dedicated to promoting a cause, to making others aware of the problem. Activists draw attention to new social problems by holding protest demonstrations, attracting media coverage, recruiting new members to their cause, lobbying officials to do something about the situation, and so on. They are the most obvious, the most visible participants in creating awareness of social problems.

    Successful activists attract support from others. The mass media—including both the press (reporters for newspapers or television news programs) and entertainment media (such as television talk shows)—relay activists' claims to the general public. Reporters often find it easy to turn those claims into interesting news stories; after all, a new social problem is a fresh topic, and it may affect lots of people, pose dramatic threats, and lead to proposals to change the lives of those involved. Media coverage, especially sympathetic coverage, can make millions of people aware of and concerned about a social problem. Activists need the media to provide that coverage, just as the media depend on activists and other sources for news to report.

    Often activists also enlist the support of experts—doctors, scientists, economists, and so on—who presumably have special qualifications to talk about the causes and consequences of some social problem. Experts may have done research on the problem and can report their findings. Activists use experts to make claims about social problems seem authoritative, and the mass media often rely on experts' testimonies to make news stories about a new problem seem more convincing. In turn, experts enjoy the respectful attention they receive from activists and the media.

    Not all social problems are promoted by struggling, independent activists; creating new social problems is sometimes the work of powerful organizations and institutions. Government officials who promote problems range from prominent politicians trying to arouse concern in order to create election campaign issues, to anonymous bureaucrats proposing that their agencies' programs be expanded to solve some social problem. And businesses, foundations, and other private organizations sometimes have their own reasons to promote particular social issues. Public and private organizations usually command the resources needed to organize effective campaigns to create social problems. They can afford to hire experts to conduct research, to sponsor and encourage activists, and to publicize their causes in ways that attract media attention.

    In other words, when we become aware of—and start to worry about—some new social problem, our concern is usually the result of efforts by some combination of problem promoters—activists, reporters, experts, officials, or private organizations—who have worked to create the sense that this is an important problem, one that deserves our attention. In this sense, people deliberately construct social problems.

    Efforts to create or promote social problems, particularly when they begin to attract attention, may inspire opposition. Sometimes this involves officials responding to critics by defending existing policies as adequate. Recall that New York police minimized the number of prostitutes in the city, just as the Reagan administration argued that activists exaggerated the number of homeless persons. In other cases, opposition comes from private interests; for example, the Tobacco Institute (funded by the tobacco industry) became notorious for, over decades, challenging every research finding that smoking was harmful.

    Statistics play an important role in campaigns to create—or defuse claims about—new social problems. Most often, such statistics describe the problem's size: there are 10,000 prostitutes in New York City, or three million homeless people. When social problems first come to our attention, perhaps in a televised news report, we're usually given an example or two (perhaps video footage of homeless individuals living on city streets) and then a statistical estimate (of the number of homeless people). Typically this is a big number. Big numbers warn us that the problem is a common one, compelling our attention, concern, and action. The media like to report statistics because numbers seem to be "hard facts"—little nuggets of indisputable truth. Activists trying to draw media attention to a new social problem often find that the press demands statistics: reporters insist on getting estimates of the problem's size—how many people are affected, how much it costs, and so on. Experts, officials, and private organizations commonly report having studied the problem, and they present statistics based on their research. Thus, the key players in creating new social problems all have reason to present statistics.

    In virtually every case, promoters use statistics as ammunition; they choose numbers that will draw attention to or away from a problem, arouse or defuse public concern. People use statistics to support their point of view, to bring others around to their way of thinking. Activists trying to gain recognition for what they believe is a big problem will offer statistics that seem to prove that the problem is indeed a big one (and they may choose to downplay, ignore, or dispute any statistics that might make it seem smaller). The media favor disturbing statistics about big problems because big problems make more interesting, more compelling news, just as experts' research (and the experts themselves) seem more important if their subject is a big, important problem. These concerns lead people to present statistics that support their position, their cause, their interests. There is an old expression that captures this tendency: "Figures may not lie, but liars figure." Certainly we need to understand that people debating social problems choose statistics selectively and present them to support their points of view. Gun-control advocates will be more likely to report the number of children killed by guns, while opponents of gun control will prefer to count citizens who use guns to defend themselves from attack. Both numbers may be correct, but most people debating gun control present only the statistic that bolsters their position.


Most claims drawing attention to new social problems aim to persuade all of us—that is, the members of the general public. We are the audience, or at least one important audience, for statistics and other claims about social problems. If the public becomes convinced that prostitution or homelessness is a serious problem, then something is more likely to be done: officials will take action, new policies will begin, and so on. Therefore, campaigns to create social problems use statistics to help arouse the public's concern.

    This is not difficult. The general public tends to be receptive to claims about new social problems, and we rarely think critically about social problems statistics. Recall that the media like to report statistics because numbers seem to be factual, little nuggets of truth. The public tends to agree; we usually treat statistics as facts.

    In part, this is because we are innumerate. Innumeracy is the mathematical equivalent of illiteracy; it is "an inability to deal comfortably with the fundamental notions of number and chance." Just as some people cannot read or read poorly, many people have trouble thinking clearly about numbers.

    One common innumerate error involves not distinguishing among large numbers. A very small child may be pleased by the gift of a penny; a slightly older child understands that a penny or even a dime can't buy much, but a dollar can buy some things, ten dollars considerably more, and a hundred dollars a great deal (at least from a child's point of view). Most adults clearly grasp what one can do with a hundred, a thousand, ten thousand, even one hundred thousand dollars, but then our imaginations begin to fail us. Big numbers blend together: a million, a billion, a trillion—what's the difference? They're all big numbers. (Actually, of course, there are tremendous differences. The difference between a million and a billion is the difference between one dollar and one thousand dollars; the difference between a million and a trillion is the difference between one dollar and a million dollars.)

    Because many people have trouble appreciating the differences among big numbers, they tend to uncritically accept social statistics (which often, of course, feature big numbers). What does it matter, they may say, whether there are 300,000 homeless or 3,000,000?—either way, it's a big number. They'd never make this mistake dealing with smaller numbers; everyone understands that it makes a real difference whether there'll be three people or thirty coming by tomorrow night for dinner. A difference (thirty is ten times greater than three) that seems obvious with smaller, more familiar numbers gets blurred when we deal with bigger numbers (3,000,000 is ten times greater than 300,000). If society is going to feed the homeless, having an accurate count is just as important as it is for an individual planning to host three—or thirty—dinner guests.

    Innumeracy—widespread confusion about basic mathematical ideas—means that many statistical claims about social problems don't get the critical attention they deserve. This is not simply because an innumerate public is being manipulated by advocates who cynically promote inaccurate statistics. Often, statistics about social problems originate with sincere, well-meaning people who are themselves innumerate; they may not grasp the full implications of what they are saying. Similarly, the media are not immune to innumeracy; reporters commonly repeat the figures their sources give them without bothering to think critically about them.

    The result can be a social comedy. Activists want to draw attention to a problem—prostitution, homelessness, or whatever. The press asks the activists for statistics—How many prostitutes? How many homeless? Knowing that big numbers indicate big problems and knowing that it will be hard to get action unless people can be convinced a big problem exists (and sincerely believing that there is a big problem), the activists produce a big estimate, and the press, having no good way to check the number, simply publicizes it. The general public—most of us suffering from at least a mild case of innumeracy—tends to accept the figure without question. After all, it's a big number, and there's no real difference among big numbers.



One reason we tend to accept statistics uncritically is that we assume that numbers come from experts who know what they're doing. Often these experts work for government agencies, such as the U.S. Bureau of the Census, and producing statistics is part of their job. Data that come from the government—crime rates, unemployment rates, poverty rates—are official statistics. There is a natural tendency to treat these figures as straightforward facts that cannot be questioned.

    This ignores the way statistics are produced. All statistics, even the most authoritative, are created by people. This does not mean that they are inevitably flawed or wrong, but it does mean that we ought to ask ourselves just how the statistics we encounter were created.

    Let's say a couple decides to get married. This requires going to a government office, taking out a marriage license, and having whoever conducts the marriage ceremony sign and file the license. Periodically, officials add up the number of marriage licenses filed and issue a report on the number of marriages. This is a relatively straightforward bit of recordkeeping, but notice that the accuracy of marriage statistics depends on couples' willingness to cooperate with the procedures. For example, imagine a couple who decide to "get married" without taking out a license; they might even have a wedding ceremony, yet their marriage will not be counted in the official record. Or consider couples that cohabit—live together—without getting married; there is no official record of their living arrangement. And there is the added problem of recordkeeping: is the system for filing, recording, and generally keeping track of marriages accurate, or do mistakes occur? These examples remind us that the official number of marriages reflects certain bureaucratic decisions about what will be counted and how to do the counting.

    Now consider a more complicated example: statistics on suicide. Typically, a coroner decides which deaths are suicides. This can be relatively straightforward: perhaps the dead individual left behind a note clearly stating an intent to commit suicide. But often there is no note, and the coroner must gather evidence that points to suicide—perhaps the deceased is known to have been depressed, the death occurred in a locked house, the cause of death was an apparently self-inflicted gunshot to the head, and so on. There are two potential mistakes here. The first is that the coroner may label a death a "suicide" when, in fact, there was another cause (in mystery novels, at least, murder often is disguised as suicide). The second possibility for error is that the coroner may assign another cause of death to what was, in fact, a suicide. This is probably a greater risk, because some people who kill themselves want to conceal that fact (for example, some single-car automobile fatalities are suicides designed to look like accidents so that the individual's family can avoid embarrassment or collect life insurance benefits). In addition, surviving family members may be ashamed by a relative's suicide, and they may press the coroner to assign another cause of death, such as accident.

    In other words, official records of suicide reflect coroners' judgments about the causes of death in what can be ambiguous circumstances. The act of suicide tends to be secretive—it usually occurs in private—and the motives of the dead cannot always be known. Labeling some deaths as "suicides" and others as "homicides," "accidents," or whatever will sometimes be wrong, although we cannot know exactly how often. Note, too, that individual coroners may assess cases differently; we might imagine one coroner who is relatively willing to label deaths suicides, and another who is very reluctant to do so. Presented with the same set of cases, the first coroner might find many more suicides than the second.


Excerpted from DAMNED LIES AND STATISTICS by Joel Best. Copyright © 2001 by The Regents of the University of California. Excerpted by permission. All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.

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Table of Contents

Introduction: The Worst Social Statistic Ever

1. The Importance of Social Statistics
2. Soft Facts: Sources of Bad Statistics
3. Mutant Statistics: Methods for Mangling Numbers
4. Apples and Oranges: Inappropriate Comparisons
5. Stat Wars: Conflicts over Social Statistics
6. Thinking about Social Statistics: The Critical Approach

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  • Anonymous

    Posted January 2, 2013

    Small Type

    I really liked this book, but there were issues with the fonts. I could only get it to display in tiny little type. My attempts to make the font bigger only messed up the margins and didn't make it large enough to read comfortably. I tried on both a Nook Simple Touch and a Nook Simple Touch with the Glowlight.

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  • Anonymous

    Posted November 1, 2012

    The most fun you'll have with statistics

    I could rant about how this book will change the way you look at the world, or how the language manages to be not only accesible but entertaining as well...but honestly, just read the first chapter. Then buy the book.

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