Statistics for Lawyers is designated to introduce law students, law teachers, practitioners, and judges to the basic ideas of mathematical probability and statistics as they as they have been applied in the law.

Includes supplementary material: sn.pub/extras

Autorentext

Michael O. Finkelstein was a practicing lawyer in New York City (now retired). He has for many years been a member of the adjunct faculty of Columbia University Law School, teaching statistics for lawyers, and has also taught that subject at Harvard University, Yale University, and the University of Pennsylvania law schools. He is the author of a book of essays, Quantitative Methods in Law, and a monograph, Basic Concepts of Probability and Statistics in the Law, as well as numerous law review articles on the applications of statistics in law. His articles have been cited by the U.S. Supreme Court and other courts. He has been for many years the editor of two law journals, The Review of Securities and Commodities Regulation and The Review of Banking and Financial Services. Bruce Levin is Professor Emeritus and past Chair of the Department of Biostatistics at the Joseph L. Mailman School of Public Health of Columbia University. He is a Fellow of the American Statistical Association and an American Public Health Association Statistics Section Award winner. Dr. Levin has a long-standing interest in statistical methodology for clinical trials, public health, and the law. Using sequential statistical methods, he has developed innovative trial designs, has served as the senior statistical designer for many randomized clinical trials, and has authored numerous articles on the subject of mathematical statistics and biostatistics. He consults and testifies as an expert in legal cases involving statistical issues.

Inhalt
Descriptive Statistics.- How to Count.- Elements of Probability.- Some Probability Distributions.- Statistical Inference for Two Proportions.- Comparing Multiple Proportions.- Comparing Means.- Combining Evidence Across Independent Strata.- Sampling Issues.- Epidemiology.- Survival Analysis.- Nonparametric Methods.- Regression Models.- More Complex Regression Models.