Statistical Reasoning in Law and Public Policy
Statistical Reasoning in Law and Public Policy

Author: Joseph L. Gastwirth

Publisher: Elsevier

Published: 1988-11-28

Total Pages: 499

ISBN-13: 0323138721

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To reach reasoned decisions involving issues of public policy and law, statistical data and studies often need to be assessed for their accuracy and relevance. This two-volume set presents a unique and comprehensive treatment of statistical methods in legal practice. Designed to serve as a text or reference, the book presents basic concepts of probability and statistical inference applied to actual data arising from court cases concerning discrimination, trademark evidence, environmental and occupational exposure to toxic chemicals, and related health and safety topics. Substantial attention is devoted to assessing the strengths and weaknesses of statistical studies, with examples illustrating why some health studies may not have been properly designed at the outset and how actual decisions might have been reversed had more appropriate analysis of data been available to the court. This book will be of interest to lawyers and other practitioners of the law, as well as to students and researchers in the areas of statistics, statistical economics, political science, and law.

Statistical Reasoning in Law and Public Policy: Statistical concepts and issues of fairness
Statistical Reasoning in Law and Public Policy: Statistical concepts and issues of fairness

Author: Joseph L. Gastwirth

Publisher:

Published: 1988

Total Pages: 520

ISBN-13:

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To reach reasoned decisions involving issues of public policy and law, statistical data and studies often need to be assessed for their accuracy and relevance. This two-volume set presents a unique and comprehensive treatment of statistical methods in legal practice. Designed to serve as a text or reference, the book presents basic concepts of probability and statistical inference applied to actual data arising from court cases concerning discrimination, trademark evidence, environmental and occupational exposure to toxic chemicals, and related health and safety topics. Substantial attention is devoted to assessing the strengths and weaknesses of statistical studies, with examples illustrating why some health studies may not have been properly designed at the outset and how actual decisions might have been reversed had more appropriate analysis of data been available to the court. This book will be of interest to lawyers and other practitioners of the law, as well as to students and researchers in the areas of statistics, statistical economics, political science, and law.

Statistical Reasoning in Law and Public Policy: Tort law, evidence, and health
Statistical Reasoning in Law and Public Policy: Tort law, evidence, and health

Author: Joseph L. Gastwirth

Publisher:

Published: 1988

Total Pages: 512

ISBN-13:

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To reach reasoned decisions involving issues of public policy and law, statistical data and studies often need to be assessed for their accuracy and relevance. This two-volume set presents a unique and comprehensive treatment of statistical methods in legal practice. Designed to serve as a text or reference, the book presents basic concepts of probability and statistical inference applied to actual data arising from court cases concerning discrimination, trademark evidence, environmental and occupational exposure to toxic chemicals, and related health and safety topics. Substantial attention is devoted to assessing the strengths and weaknesses of statistical studies, with examples illustrating why some health studies may not have been properly designed at the outset and how actual decisions might have been reversed had more appropriate analysis of data been available to the court. This book will be of interest to lawyers and other practitioners of the law, as well as to students and researchers in the areas of statistics, statistical economics, political science, and law.

Statistics for Lawyers
Statistics for Lawyers

Author: Michael O. Finkelstein

Publisher: Springer

Published: 2015-12-16

Total Pages: 679

ISBN-13: 1441959858

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This classic text, first published in 1990, is 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 third edition includes over twenty new sections, including the addition of timely topics, like New York City police stops, exonerations in death-sentence cases, projecting airline costs, and new material on various statistical techniques such as the randomized response survey technique, rare-events meta-analysis, competing risks, and negative binomial regression. The book consists of sections of exposition followed by real-world cases and case studies in which statistical data have played a role. The reader is asked to apply the theory to the facts, to calculate results (a hand calculator is sufficient), and to explore legal issues raised by quantitative findings. The authors' calculations and comments are given in the back of the book. As with previous editions, 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, sampling for insurance audits, and the death penalty. A chapter on epidemiology was added in the second edition. In 1991, the first edition was selected by the University of Michigan Law Review as one of the important law books of the year.

Statistics and the Evaluation of Evidence for Forensic Scientists
Statistics and the Evaluation of Evidence for Forensic Scientists

Author: Colin Aitken

Publisher: John Wiley & Sons

Published: 2020-11-24

Total Pages: 1248

ISBN-13: 1119245257

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The leading resource in the statistical evaluation and interpretation of forensic evidence The third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That’s why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It’s written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence. Discusses the entire chain of reasoning–from evidence pre-assessment to court presentation; Includes material for the understanding of evidence interpretation for single and multiple trace evidence; Provides real examples and data for improved understanding. Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.

Statistical Science in the Courtroom
Statistical Science in the Courtroom

Author: Joseph L. Gastwirth

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 454

ISBN-13: 1461212162

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Expert testimony relying on scientific and other specialized evidence has come under increased scrutiny by the legal system. A trilogy of recent U.S. Supreme Court cases has assigned judges the task of assessing the relevance and reliability of proposed expert testimony. In conjunction with the Federal judiciary, the American Association for the Advancement of Science has initiated a project to provide judges indicating a need with their own expert. This concern with the proper interpretation of scientific evidence, especially that of a probabilistic nature, has also occurred in England, Australia and in several European countries. Statistical Science in the Courtroom is a collection of articles written by statisticians and legal scholars who have been concerned with problems arising in the use of statistical evidence. A number of articles describe DNA evidence and the difficulties of properly calculating the probability that a random individual's profile would "match" that of the evidence as well as the proper way to intrepret the result. In addition to the technical issues, several authors tell about their experiences in court. A few have become disenchanted with their involvement and describe the events that led them to devote less time to this application. Other articles describe the role of statistical evidence in cases concerning discrimination against minorities, product liability, environmental regulation, the appropriateness and fairness of sentences and how being involved in legal statistics has raised interesting statistical problems requiring further research.

Bayesian Ideas and Data Analysis
Bayesian Ideas and Data Analysis

Author: Ronald Christensen

Publisher: CRC Press

Published: 2011-07-07

Total Pages: 518

ISBN-13: 1439803552

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Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to collaborate in analyzing data. The WinBUGS code provided offers a convenient platform to model and analyze a wide range of data. The first five chapters of the book contain core material that spans basic Bayesian ideas, calculations, and inference, including modeling one and two sample data from traditional sampling models. The text then covers Monte Carlo methods, such as Markov chain Monte Carlo (MCMC) simulation. After discussing linear structures in regression, it presents binomial regression, normal regression, analysis of variance, and Poisson regression, before extending these methods to handle correlated data. The authors also examine survival analysis and binary diagnostic testing. A complementary chapter on diagnostic testing for continuous outcomes is available on the book’s website. The last chapter on nonparametric inference explores density estimation and flexible regression modeling of mean functions. The appropriate statistical analysis of data involves a collaborative effort between scientists and statisticians. Exemplifying this approach, Bayesian Ideas and Data Analysis focuses on the necessary tools and concepts for modeling and analyzing scientific data. Data sets and codes are provided on a supplemental website.

Optimization Techniques in Statistics
Optimization Techniques in Statistics

Author: Jagdish S. Rustagi

Publisher: Elsevier

Published: 2014-05-19

Total Pages: 376

ISBN-13: 1483295710

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Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimization in function spaces are also discussed, as are stochastic optimization in simulation, including annealing methods. The text features numerous applications, including: Finding maximum likelihood estimates, Markov decision processes, Programming methods used to optimize monitoring of patients in hospitals, Derivation of the Neyman-Pearson lemma, The search for optimal designs, Simulation of a steel mill. Suitable as both a reference and a text, this book will be of interest to advanced undergraduate or beginning graduate students in statistics, operations research, management and engineering sciences, and related fields. Most of the material can be covered in one semester by students with a basic background in probability and statistics. - Covers optimization from traditional methods to recent developments such as Karmarkars algorithm and simulated annealing - Develops a wide range of statistical techniques in the unified context of optimization - Discusses applications such as optimizing monitoring of patients and simulating steel mill operations - Treats numerical methods and applications - Includes exercises and references for each chapter - Covers topics such as linear, nonlinear, and dynamic programming, variational methods, and stochastic optimization

Sample Size Methodology
Sample Size Methodology

Author: M. M. Desu

Publisher: Elsevier

Published: 2012-12-02

Total Pages: 151

ISBN-13: 0323139566

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One of the most important problems in designing an experiment or a survey is sample size determination and this book presents the currently available methodology. It includes both random sampling from standard probability distributions and from finite populations. Also discussed is sample size determination for estimating parameters in a Bayesian setting by considering the posterior distribution of the parameter and specifying the necessary requirements. The determination of the sample size is considered for ranking and selection problems as well as for the design of clinical trials. Appropriate techniques for attacking the general question of sample size determination in problems of estimation, tests of hypotheses, selection, and clinical trial design are all presented, and will help the reader in formulating an appropriate problem of sample size and in obtaining the solution. The book can be used as a text in a senior-level or a graduate course on sample size methodology.Annotated list of tables in appendixSupplemental problems at the end of book