Statistical Methods in Discrimination LitigationCRC Press, 07.08.1986 - 232 Seiten Helping expert witnesses and consultants fulfill their professional responsibility by choosing the best statistical method for specific legal situations, this valuable reference surveys the most common methods already in use, describes their flaws and problems, anticipates significant new difficulties not previously identified, and supports the development and application of more refined techniques suited to the phenomena of discrimination. Statistical Methods in Discrimination Litigation considers the legal theories that underlie the collection and analysis of data for courtroom use ... discusses essential statistical techniques, such as the odds ratio, Mantel-Haenszel test, multiple linear regression analyses, competing psychometric concepts of fairness, and more ... outlines means of improving statistical presentations in court by more sophisticated data analysis techniques ... and brings together materials and references from law, statistics, and psychology in a unique synthesis. Introducing statisticians and social scientists to the legal concepts and methodological issues necessary for proving or rebutting claims of discrimination with statistical evidence, Statistical Methods in Discrimination Litigation is an important reference for applied statisticians; economists; psychologists; sociologists; attorneys and judges involved in discrimination litigation as well as experts who consult or testify in discrimination cases; advanced undergraduate statistics courses; and law school and graduate economics seminars on discrimination. Book jacket. |
Inhalt
Statistical Evidence of Discrimination in Jury Selection | 13 |
Claims of Employment Discrimination Under Title VII | 33 |
Defining the Relevant Population in Employment | 55 |
Regression Analysis in Discrimination Cases | 69 |
The Perverse Logic of Reverse Regression | 85 |
Measurement Error and Regression Analysis | 107 |
viii | 129 |
Validating Employee Selection Procedures | 133 |
Issues and Methods in Discrimination Statistics | 159 |
| 211 | |
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adverse impact affirmative action Albemarle Paper Co assumption average b₁ b₂ bias biased blacks burden claims of disparate coefficient construct validation content validation correlation criterion criterion validation data set depends detect direct regression discriminatory disparate impact disparate treatment effect employees Employment Discrimination employment practice equal equation estimate example expected fairness females Figure frequentist gender grand jury hiring Hispanics hypothesis testing indicate inference issue job analysis job performance jurors least squares males Mantel-Haenszel Measurement Error nonsuspect null hypothesis observed P-values parameter plaintiff probabilistic probability problem productivity professional jobs proportion proxy qualifications question race racial random regres regression analysis regression model relevant population requirement reverse regression salary sample scores Section selection procedure Simpson's paradox ẞ₁ ẞp standard statistical evidence statistical methods statistician Supreme Court suspect class Table tion Title VII UGESP unfairness Uniform Guidelines variables venires women zero