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In the wrong hands, math can be deadly. Even the simplest numbers can become powerful forces when manipulated by journalists, politicians or other public figures, but in the case of the law your liberty—and your life—can depend on the right calculation. Math on Trial tells the story of ten trials in which mathematical arguments were used—and disastrously misused—as evidence. Despite years of math classes, most people (and most jurors) fail to detect even simple mathematical sophistry, resulting in such horrors as a medical expert’s faulty calculation of probabilities providing the key evidence for a British mother’s conviction for the murder of her two babies. The conviction was later overturned, but three years in prison took its toll—Sally Clark died of acute alcohol intoxication in March of 2007. Mathematicians Leila Schneps and Coralie Colmez use a wide range of examples, from a mid-19th-century dispute over wills that became a signal case in the forensic use of mathematics, to the conviction and subsequent exoneration of Amanda Knox, to show how the improper application of mathematical concepts can mean the difference between walking free and life in prison. The cases discussed include: -The Case of Amanda Knox (How a judge’s denial of a second DNA test may have destroyed a chance to reveal the truth about Meredith Kercher’s murder) -The Case of Joe Sneed (How a fabricated probability framed a son for his parents’ grisly killing) -The Case of Sally Clark (How multiplying non-independent probabilities landed an innocent mother in jail for the murder of her children) -The Case of Janet Collins (How unjustified estimates combined with a miscalculated probability convicted an innocent couple of violent robbery) A colorful narrative of mathematical abuse featuring such characters as Charles Ponzi, Alfred Dreyfus, Hetty Green, and Oliver Wendell Holmes, Math on Trial shows that legal expertise isn’t everything when it comes to proving a man innocent.
Describes the issues that can result when mathematical arguments are improperly used and discusses ten trials where this was the case, including the Dreyfus Affair, the case of Diana Sylvester, and Charles Ponzi's original scheme.
In the wrong hands, math can be deadly. Even the simplest numbers can become powerful forces when manipulated by journalists, politicians or other public figures, but in the case of the law your liberty—and your life—can depend on the right calculation. Math on Trial tells the story of ten trials in which mathematical arguments were used—and disastrously misused—as evidence. Despite years of math classes, most people (and most jurors) fail to detect even simple mathematical sophistry, resulting in such horrors as a medical expert’s faulty calculation of probabilities providing the key evidence for a British mother’s conviction for the murder of her two babies. The conviction was later overturned, but three years in prison took its toll—Sally Clark died of acute alcohol intoxication in March of 2007. Mathematicians Leila Schneps and Coralie Colmez use a wide range of examples, from a mid-19th-century dispute over wills that became a signal case in the forensic use of mathematics, to the conviction and subsequent exoneration of Amanda Knox, to show how the improper application of mathematical concepts can mean the difference between walking free and life in prison. The cases discussed include: -The Case of Amanda Knox (How a judge’s denial of a second DNA test may have destroyed a chance to reveal the truth about Meredith Kercher’s murder) -The Case of Joe Sneed (How a fabricated probability framed a son for his parents’ grisly killing) -The Case of Sally Clark (How multiplying non-independent probabilities landed an innocent mother in jail for the murder of her children) -The Case of Janet Collins (How unjustified estimates combined with a miscalculated probability convicted an innocent couple of violent robbery) A colorful narrative of mathematical abuse featuring such characters as Charles Ponzi, Alfred Dreyfus, Hetty Green, and Oliver Wendell Holmes, Math on Trial shows that legal expertise isn’t everything when it comes to proving a man innocent.
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.
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.
When as a practicing lawyer I published my ?rst article on statistical evidence in 1966, the editors of the Harvard Law Review told me that a mathematical equa- 1 tion had never before appeared in the review. This hardly seems possible - but if they meant a serious mathematical equation, perhaps they were right. Today all that has changed in legal academia. Whole journals are devoted to scienti?c methods in law or empirical studies of legal institutions. Much of this work involves statistics. Columbia Law School, where I teach, has a professor of law and epidemiology and other law schools have similar “law and” professorships. Many offer courses on statistics (I teach one) or, more broadly, on law and social science. The same is true of practice. Where there are data to parse in a litigation, stat- ticians and other experts using statistical tools now frequently testify. And judges must understand them. In 1993, in its landmark Daubert decision, the Supreme Court commanded federal judges to penetrate scienti?c evidence and ?nd it “re- 2 liable” before allowing it in evidence. It is emblematic of the rise of statistics in the law that the evidence at issue in that much-cited case included a series of epidemiological studies. The Supreme Court’s new requirement made the Federal Judicial Center’s Reference Manual on Scienti?c Evidence, which appeared at about the same time, a best seller. It has several important chapters on statistics.
Fair Division, unlike most research on fairness in the social sciences and mathematics, is devoted solely to the analysis of constructive procedures for actually dividing things up and resolving disputes, including indivisible items or issues, such as the marital property in a divorce or sovereignty in an international dispute.

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