Damned Lies and Statistics
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"A real page-turner. Best is the John Grisham of sociology!" - James Holstein, author of The New Language of Qualitative Method "Best continues to invite us to participate in his absolutely fascinating and sobering quest into the fantastic differences between the world as it is and the world as it is portrayed in the statistics the media use....This book is simply a must." - Nachman Ben-Yehuda, author of The Madada Myth "Best is our leading authority on social problems today. His detective work in exposing the spurious use of statistics is essential to constructive social science. No one who speaks for the public welfare can ignore his powerful work." - Jonathan B.Imber, Editor in Chief, Society "Joel 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." - Patricia Adler, author of Peer Power"
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Does the number of children gunned down double each year? Does anorexia kill 150,000 young women annually? Do white males account for only a sixth of new workers? Startling statistics shape our thinking about social issues. But all too often, these numbers are wrong. This book is a lively guide to spotting bad statistics and learning to think critically about these influential numbers. "Damned Lies and Statistics" is essential reading for everyone who reads or listens to the news, for students, and for anyone who relies on statistical information to understand social problems. Joel Best bases his discussion on a wide assortment of intriguing contemporary issues that have garnered much recent media attention, including abortion, cyberporn, homelessness, the Million Man March, teen suicide, the U.S. census, and much more. Using examples from the "New York Times", the "Washington Post", and other major newspapers and television programs, he unravels many fascinating examples of the use, misuse, and abuse of statistical information. In this book Best shows us exactly how and why bad statistics emerge, spread, and come to shape policy debates. He recommends specific ways to detect bad statistics, and shows how to think more critically about 'stat wars', or disputes over social statistics among various experts. Understanding this book does not require sophisticated mathematical knowledge; Best discusses the most basic and most easily understood forms of statistics, such as percentages, averages, and rates. This accessible book provides an alternative to either naively accepting the statistics we hear or cynically assuming that all numbers are meaningless. It shows how anyone can become a more intelligent, critical, and empowered consumer of the statistics that inundate both the social sciences and our media-saturated lives.
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Nineteenth-century Americans worried about prostitution; reformers called it "the social evil" and warned that many women prostituted themselves. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Nineteenth-century Americans worried about prostitution; reformers called it "the social evil" and warned that many women prostituted themselves. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Most Helpful Customer Reviews
37 of 38 people found the following review helpful:
5.0 out of 5 stars
Understanding statistics for good decisions,
By Ken Friedman "Ken Friedman" (Oslo, Norway, and Copenhagen, Denmark) - See all my reviews (REAL NAME)
This review is from: Damned Lies and Statistics: Untangling Numbers from the Media, Politicians and Activists (Hardcover)
This is a book about reading and understanding statistics. It is not a book on research methods. As a book that helps to analyze and think critically about statistics, however, it is a book on methodology: the critical comparison of method issues.Best's point is a central issue in modern industrial democracy. If we are going to make effective policy choices as citizens and voters, we must understand the issues on which we make decisions. The same holds true for the decisions we make in business life and in research. Many of the choices we make are based on statistical evidence. To make informed choices, therefore, we must be able to think about statistics. A quick summary of the issues and topics in this book offers a good overview of clear thinking on statistical issues. Chapter 1, "the importance of social statistics," explains where statistics come from, how we use them, and why they are important. Chapter 2, "soft facts," discusses sources of bad statistics. Guessing, poor definitions, poor measures, and bad samples are the primary sources of based statistics. Good statistics require good data; clear, reasonable definitions; clear, reasonable measures; and appropriate samples. Chapter 3 catalogues "mutant statistics," the methods for mangling numbers. Most of these arise from violating the four requirements of good statistics, but a new problem arises here. Where is relatively easy to spot bad statistics, mutant statistics require a second level of understanding. As statistics mutate, they take on a history, and it becomes necessary to unravel the history to understand just how - and why - they are mutant. Transformation, confusion, and compound errors create chains of based statistics that become difficult to trace and categorize. Chapter 4, "apples and oranges," describes the dangers of inappropriate comparison. Dangers arise when comparisons over time involve changing and unchanging measures, and projections. Comparison among places and groups lead to problems not merely in the data measured, but in the ways that data may be gathered and collated. Comparison among social problems also creates unique difficulties. Best offers logic of comparison to help the reader understand how to make sense of good comparison and bad. Chapter 5, "stat wars," describes the problems that arise when advocates use questionable numbers to make a case. Chapter 6, "thinking about social statistics," sums up Best's advice on understanding statistics. Don't be awestruck in the face of numbers, and don't be cynical about them, he suggests. Be critical and thoughtful. This book is recommended for every non-statistical researcher who is required to make some use of statistical results in his or her work. It will be especially helpful for those designers who belong to the 2% of the population that one study identifies as victims of UFO abduction. Ken Friedman Professor Norwegian School of Management, Oslo, and Denmark's Design School, Copenhagen This review originally appeared in Design Research News
1 of 1 people found the following review helpful:
5.0 out of 5 stars
Awe-struck by big numbers,
This review is from: Damned Lies and Statistics: Untangling Numbers from the Media, Politicians and Activists (Hardcover)
The indelicate title of this book is taken from the well-known aphorism "There are lies, damned lies, and statistics" attributed to either Mark Twain or Benjamin Disraeli. It nearly caused me to not read it, unjustly, because the language between the covers is perfectly gentlemanly.Most people, Best tells us, are innumerate. This means that they don't readily spot implausible numbers, and all big numbers are more or less the same to them, whether a million or a billion. Not only the people who hear statistics are often innumerate, but also the people who report them, and not infrequently even the people who generate them. Statistics can be wildly off course for many reasons. They may originate in a guess. But even when they originate in research, there are many factors that can influence their accuracy. The researcher may have interviewed people using leading questions. The subject of the research may be poorly defined. The method of measuring it may be flawed. The sample on which the research is based may not be representative. Or perhaps a comparison was made between two entities that aren't comparable. Numbers may have been mangled by someone who quoted them, such as a reporter. Or the condition described mutates into something else during the retelling. The finesses of complex statistics may be overlooked. Basing new statistics on older ones may result in a chain of bad statistics. And, unavoidably, they are influenced by the interests of the party who compiles them. The author does not mention the statistics used in modern medical mega-trials, but everything he says about statistics in general applies to those as well. He warns us not to be naïve or awestruck by statistics, but not to be cynical either. Statistics, he says, are a valid and useful tool. Not all statistics are bad statistics. So we shouldn't reject all statistics off the bat, just be critical. Of course we should always be critical about everything anyway, he concedes, not just about statistics. I'm afraid I'm not going to take Best's advice. He provides fine questions to ask when examining statistics, but who will answer them? So I am going to join his cynical group, and remain suspicious of all statistics. Best's writing style is refreshingly uncomplicated. This little gem of a book is suitable for a broad audience, including the less sophisticated reader, readers for whom English is a second language, and people who, like me, are innumerate. Best has since (2004) published a sequel to this book, called More Damned Lies and Statistics. Copyright © MeTZelf
1 of 1 people found the following review helpful:
4.0 out of 5 stars
Great book for social statistics,
By
This review is from: Damned Lies and Statistics: Untangling Numbers from the Media, Politicians and Activists (Hardcover)
This is an excellent book describing the social side of statistics - a real eye-opener making us all remember that statistics are not perhaps as 'concrete' as we first thought. Although statistics may be calculated, in some sense precisely and numerically, this book reminds us that however precise the numbers seem to be, they are based on people's definitions and driven by their motivations, and we should bear this in mind when interpreting statistics.
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