MARC Record from harvard_bibliographic_metadata

LEADER: 02091cam a22002654a 4500
001 011502119-1
005 20081017095736.0
008 080416s2008 caua b s001 0 eng
010 $a 2008017175
020 $a9780520257467 (cloth : alk. paper)
020 $a0520257464 (cloth : alk. paper)
035 0 $aocn225846896
040 $aDLC$cDLC$dBTCTA$dBAKER$dYDXCP$dUKM$dC#P$dBWX
050 00 $aHM535$b.B477 2008
082 00 $a301.072/7$222
100 1 $aBest, Joel.
245 10 $aStat-spotting :$ba field guide to identifying dubious data /$cJoel Best.
260 $aBerkeley :$bUniversity of California Press,$cc2008.
300 $a132 p. :$bill. ;$c22 cm.
504 $aIncludes bibliographical references (p. 119-129) and index.
505 0 $aGetting started -- Spotting questionable numbers -- Background -- Statistical benchmarks -- Severity and frequency -- Varieties of dubious data -- Blunders -- The slippery decimal point -- Botched translations -- Misleading graphs -- Careless calculations -- Sources: who counted--and why? -- Big round numbers -- Hyperbole -- Shocking claims -- Naming the problem -- Definitions: what did they count? -- Broad definitions -- Expanding definitions -- Changing definitions -- The uncounted -- Measurements: how did they count? -- Creating measures -- Odd units of analysis -- Loaded questions -- Raising the bar -- Technical measures -- Packaging: what are they telling us? -- Impressive formats -- Misleading samples -- Convenient time frames -- Peculiar percentages -- Selective comparisons -- Statistical milestones -- Averages -- Epidemics -- Correlations -- Discoveries -- Debates: what if they disagree? -- Causality debates -- Equality debates -- Policy debates -- Stat-spotting on your own -- Summary: common signs of dubious data -- Better data: some characteristics -- Afterword: if you had no idea things were that bad, they probably aren't -- Suggestions for those who want to continue stat-spotting.
650 0 $aSociology$xStatistical methods.
650 0 $aSocial problems$xStatistical methods.
988 $a20080627
906 $0DLC