UID:
almahu_9947362851402882
Umfang:
XXIII, 353 p.
,
online resource.
ISBN:
9781461218241
Serie:
Statistics for Social Science and Public Policy
Inhalt:
"Prove It With Figures" displays some of the tools of the social and statistical sciences that have been applied to the proof of facts in the courtroom and to the study of questions of legal importance. It explains how researchers can extract the most valuable and reliable data that can conveniently be made available, and how these efforts sometimes go awry. In the tradition of Zeisel's "Say It with Figures," a standard in the field of social statistics since 1947, it clarifies, in non-technical language, some of the basic problems common to all efforts to discern cause-and-effect relationships. Designed as a textbook for law students who seek an appreciation of the power and limits of empirical methods, the work also is a useful reference for lawyers, policymakers, and members of the public who would like to improve their critical understanding of the statistics presented to them. The many case histories include analyses of the death penalty, jury selection, employment discrimination, mass torts, and DNA profiling. Hans Zeisel was Professor of Law and Sociology Emeritus at the University of Chicago, where he pioneered the application of social science to the law. Earlier, he had a distinguished career in public opinion and market research. He has written on a wide variety of topics, ranging from research methodology and history to law enforcement, juries, and Sheakespeare. He was elected Fellow of the American Statistical Assoication and the American Association for the Advancement of Science, and in 1980 he was inducted into the Market Research Hall of Fame. David Kaye is Regents Professor at the Arizona State University, where he teaches evidence and related topics. An author of several law textbooks and treatises, his work also has appeared in journals of.
Anmerkung:
1 The Search for Causes: An Overview -- 2 The Controlled Randomized Experiment -- 2.1 A nearly perfect experiment -- 2.2 Eliminating bias in selecting subjects -- 2.3 Limits to experimentation -- 2.4 The half-a-loaf experiment -- 2.5 Simulation -- 2.6 Limits to extrapolation -- Critical questions -- 3 Inferring Causes from Observational Studies -- 3.1 Diphtheria antitoxin -- 3.2 The Connecticut crackdown on speeders -- 3.3 Capital punishment in Florida -- 3.4 Polio vaccines -- 3.5 Police intervention and domestic violence -- 3.6 No-fault divorce -- 3.7 Statistical “control” for known confounders -- 3.8 Summary -- Critical questions -- 4 Epidemiologic Studies -- 4.1 Types of studies -- 4.2 Agent Orange -- 4.3 Breast implants -- 4.4 Tobacco smoke -- 4.5 Asbestos -- 4.6 Bendectin -- 4.7 Electromagnetic fields -- 4.8 Summary -- 5 Summing Up: Replication and Triangulation -- 5.1 Estimating socially significant numbers -- 5.2 Triangulations in the census -- 5.3 Unanimity and hung juries -- 5.4 Opposition to the death penalty and -- the propensity to vote guilty -- 5.5 Sentence variation from judge to judge -- 6 Coincidence and Significance -- 6.1 P-values -- 6.2 Significance -- 6.3 Power -- 6.4 One-tailed and two-tailed tests -- 6.5 Multiple testing -- 6.6 Interval estimates -- 6.7 Other hypotheses -- 6.8 Posterior probabilities -- Critical questions -- 7 Sampling -- 7.1 The road to the acceptance of sampling -- 7.2 The miracle of sampling -- 7.3 Some sources of bias -- 7.4 Drawing a probability sample -- 7.5 Sample size -- 7.6 The danger of mail surveys: nonresponse bias -- 7.7 Quota samples -- 7.8 Convenience samples -- 7.9 Summary -- Critical questions -- 8 Content Analysis -- 8.1 A study of the House Un-American -- Activities Committee -- 8.2 Pretrial publicity -- 8.3 The Federalist Papers -- 9 Surveys and Change of Venue -- 9.1 History of survey acceptance -- 9.2 Change of venue law -- 9.3 Mitsubishi in Silicon Valley -- 9.4 The Pontiac prison cases -- 9.5 Civil litigation -- 9.6 The limits of voir dire -- 10 Trademark Surveys: Genericness -- 10.1 The Thermos surveys -- 10.2 The Teflon surveys -- 10.3 Variations of the Teflon survey -- 11 Trademark Surveys: Confusion -- 11.1 Realism -- 11.2 How close a look? -- 11.3 Who puts out this design? -- 11.4 Altering the specimen -- 11.5 Controlling for “top of mind” responses -- 11.6 Anticipating market entry -- 11.7 Addressing the relevant issue -- 11.8 Depressors and aggrandizers -- 11.9 Summary -- 12 The Jury: Composition and Selection -- 12.1 Jury size -- 12.2 Selecting the jury venire -- 12.3 Selecting from the venire -- 12.4 Juror selection surveys -- 13 DNA Profiling: Probabilities and Proof -- 13.1 VNTR profiling -- 13.2 Match windows -- 13.3 Match probabilities and the basic product rule -- 13.4 Objections to the basic product rule -- 13.5 Ceiling frequencies -- 13.6 Uniqueness -- 13.7 Random match probabilities and prejudice -- 13.8 Beyond matching and binning -- Notes -- List of Cases.
In:
Springer eBooks
Weitere Ausg.:
Printed edition: ISBN 9781461273004
Sprache:
Englisch
DOI:
10.1007/978-1-4612-1824-1
URL:
http://dx.doi.org/10.1007/978-1-4612-1824-1
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