法律家のための統計学(第2版)<br>Statistics for Lawyers (Statistics for Social Science and Public Policy) (New ed. 2007. XXII, 608 S. m. 39 Abb. 23,5 cm)

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法律家のための統計学(第2版)
Statistics for Lawyers (Statistics for Social Science and Public Policy) (New ed. 2007. XXII, 608 S. m. 39 Abb. 23,5 cm)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 450 p.
  • 商品コード 9780387950075

基本説明

Originally published in the series: Springer Texts in Statistics. The cases and case studies reflect a broad variety of legal subjects, including anti-discrimination, mass torts, taxation, school finance, identification evidence, preventive detention, handwriting disputes, etc.

Full Description


Designed to introduce law students, law teachers, practitioners, and judges to the basic ideas of mathematical probability and statistics as they have been applied in the law, the book consists of sections of exposition followed by real-world cases and case studies in which stastical data have played a role. Readers are asked to apply the theory to the facts, to calculate results (a pocket calculator is sufficient), and to explore legal issues raised by quantitative findings, while the author's own calculations and comments are given in the back of the book. The cases and case studies reflect a broad variety of legal subjects, including antidiscrimination, mass torts, taxation, school finance, identification evidence, preventive detention, handwriting disputes, voting, environmental protection, antitrust, and the death penalty. The first edition has been used in law, statistics, and social science courses, and in 1991 was selected by the University of Michigan Law Review as one of the important law books of the year. This second edition includes many new problems reflecting current developments in the law, including a new chapter on epidemiology.

Contents

Describing Data.- Inferring Causation.- How to CountCombinations.- Elements of Probability.- Some Probability Distributions.- Statistical Inference for Two Proportions.- Comparing Multiple Proportions.- Comparing Means.- Combining Evidence Across Independent Strata.- Sampling Issues.- Survival Analysis.- Nonparametric Methods.- Regression Models.