Are four million women really battered to death by their husbands or boyfriends each year? Does a young person commit suicide every thirteen minutes in the United States? 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. Following on the heels of his highly acclaimed Damned Lies and Statistics and More Damned Lies and Statistics, Joel Best now offers this practical field guide to help everyone identify questionable statistics. Entertaining, informative, and concise, Stat-Spotting is essential reading for people who want to be more savvy and critical consumers of news and information.

pt. 1.A. B. B.1. B.2. pt. 2. C. C.1. The C.2. C.3. C.4. D. D.1. D.2. D.3. D.4. E. E.1. E.2. E.3. E.4. The F. F.1. F.2. F.3. F.4. F.5. Technical measures -- pt. 1. Getting started -- A. Spotting questionable numbers -- B. Background -- B.1. Statistical benchmarks -- B.2. Severity and frequency -- pt. 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. Debates : what if they disagree? -- H.1. Causality debates -- H.2. Equality debates -- H.3. Policy debates -- pt. 3. Stat-spotting on your own -- I. Summary : Common signs of dubious data -- J. Better data : some characteristics -- K. Afterword : If you had no idea things were that bad, they probably aren't -- L. Suggestions for those who want to continue stat-spotting -- Acknowledgments -- Notes -- Index. G. G.1. G.2. G.3. G.4. G.5. G.6. G.7. G.8. G.9. G.10. H. Debates : what if they disagree? -- H.1. H.2. H.3. pt. 3. I. J. K. L. Suggestions for those who want to continue stat-spotting -- Acknowledgments -- Notes -- Index.