Stat-Spotting

Does a young person commit suicide every thirteen minutes in the United States? Are four million women really battered to death by their husbands or boyfriends each year? Is methamphetamine our number one drug problem today? Alarming statistics bombard our daily lives, appearing in the news, on the Web, seemingly everywhere. But all too often, even the most respected publications present numbers that are miscalculated, misinterpreted, hyped, or simply misleading.

This new edition contains revised benchmark statistics, updated resources, and a new section on the rhetorical uses of statistics, complete with new problems to be spotted and new examples illustrating those problems. Joel Best’s best seller exposes questionable uses of statistics and guides the reader toward becoming a more critical, savvy consumer of news, information, and data.

Entertaining, informative, and concise, Stat-Spotting takes a commonsense approach to understanding data and doesn't require advanced math or statistics.

Joel Best is Professor of Sociology and Criminal Justice at the University of Delaware. Among his many books are Flavor of the Month: Why Smart People Fall for Fads, More Damned Lies and Statistics: How Numbers Confuse Public Issues, and Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists, all from UC Press.

PREFACE TO THE 2013 EDITION

PART 1. GETTING STARTED
A. SPOTTING QUESTIONABLE NUMBERS
B. BACKGROUND
B.1 Statistical Benchmarks
B.2 Severity and Frequency

PART 2. VARIETIES OF DUBIOUS DATA
C. BLUNDERS
C.1 The Slippery Decimal Point
C.2 Botched Translations
C.3 Misleading Graphs
C.4 Careless Calculations

D. SOURCES: WHO COUNTED–AND WHY?
D.1 Big Round Numbers
D.2 Hyperbole
D.3 Shocking Claims
D.4 Naming the Problem

E. DEFINITIONS: WHAT DID THEY COUNT?
E.1 Broad Definitions
E.2 Expanding Definitions
E.3 Changing Definitions
E.4 The Uncounted

F. MEASUREMENTS: HOW DID THEY COUNT?
F.1 Creating Measures
F.2 Odd Units of Analysis
F.3 Loaded Questions
F.4 Raising the Bar
F.5 Technical Measures

G. PACKAGING: WHAT ARE THEY TELLING US?
G.1 Impressive Formats
G.2 Misleading Samples
G.3 Convenient Time Frames
G.4 Peculiar Percentages
G.5 Selective Comparisons
G.6 Statistical Milestones
G.7 Averages
G.8 Epidemics
G.9 Correlations
G.10 Discoveries

H. RHETORIC: WHAT DO THEY WANT US TO THINK?
H.1 Using Short-Term Turnover to Measure Long-Term Problems
H.2 Sudden Turns for the Worse
H.3 Designating Myths
H.4 Rhetorical Flourishes

I. DEBATES: WHAT IF THEY DISAGREE?
I.1 Causality Debates
I.2 Equality Debates
I.3 Policy Debates

PART 3. STAT-SPOTTING ON YOUR OWN
J. SUMMARY: COMMON SIGNS OF DUBIOUS DATA
K. BETTER DATA: SOME CHARACTERISTICS
L. AFTERWORD: IF YOU HAD NO IDEA THINGS WERE THAT BAD, THEY PROBABLY AREN’T
M. SUGGESTIONS FOR THOSE WHO WANT TO CONTINUE STAT-SPOTTING

ACKNOWLEDGMENTS
NOTES
INDEX