Joseph B. Kadane – författare

The book will serve primarily as a user's manual or desk reference for the expert witness-lawyer team and secondarily as a textbook or supplemental textbook for upper level undergraduate statistics students. It starts with two articles by masters of the trade, Paul Meier and Franklin Fisher. It then explains the distinction between the Frye and Daughbert standards for expert testimony, and how these standards play out in court. The bulk of the book is concerned with individual cases ranging over a wide variety of topics, such as electronic draw poker (does it require skill to play), employment discrimination (how to tell whether an employer discriminated against older workers in deciding whom to fire), driving while black (did the New Jersey State Police disproportionately stop blacks), jury representativeness (is a jury a representative cross section of the community), juries hearing death penalty cases (are such juries biased toward a guilty verdict, and does the Supreme Court care), the civil incarceration of violent sexual offenders after having served their jail sentences (can future dangerousness be predicted), do data from multiple choice examinations support an allegation of copying, whether rental agents in an apartment complex steered African-American prospects to one part of the complex, how much tax is owed after an audit that used a random sample, whether an inventor falsified his notebook in an effort to fool the Patent Office, and whether ballots had been tampered with in an election. The book concludes with two recent English cases, one in which a woman was accused of murdering her infant sons because both died of "cot death" or "sudden death syndrome", (she was convicted, but later exonerated), and how Bayesian analyses can (or more precisely), cannot be presented in UK courts. In each study, the statistical analysis is shaped to address the relevant legal questions, and draws on whatever methods in statistics might shed light on those questions.

Praise for the first edition: Principles of Uncertaintyis a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. … the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. … A must-read for sure!—Christian Robert, CHANCEIt's a lovely book, one that I hope will be widely adopted as a course textbook.—Michael Jordan, University of California, Berkeley, USALike the prize-winning first edition, Principles of Uncertainty, Second Edition is an accessible, comprehensive text on the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples. It presents an introduction to the subjective Bayesian approach which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. This new edition has been updated throughout and features new material on Nonparametric Bayesian Methods, the Dirichlet distribution, a simple proof of the central limit theorem, and new problems.Key Features: First edition won the 2011 DeGroot Prize Well-written introduction to theory of Bayesian statistics Each of the introductory chapters begins by introducing one new concept or assumption Uses "just-in-time mathematics"—the introduction to mathematical ideas just before they are applied

A fair question to ask of an advocate of subjective Bayesianism (which the author is) is "how would you model uncertainty?" In this book, the author writes about how he has done it using real problems from the past, and offers additional comments about the context in which he was working.

Describes a wide variety of applications of statistical concepts in legal settings, as well as cases in which statistical analyses were important elements. Several chapters are devoted to employment discrimination and antitrust violation, two areas of litigation that rely heavily on statistics. Contributors discuss the correct choice and use of statistical techniques in the assessment of damages, the measurement and quantification of skill (in a case deciding whether video poker games require skill), the determination of disputed paternity and elections, and other areas where statistics are used in legal cases. Many of the chapters are written by the statisticians who actually participated in the cases under discussion.

How to conduct clinical trials in an ethical and scientificallyresponsible manner This book presents a methodology for clinical trials that producesimproved health outcomes for patients while obtaining sound andunambiguous scientific data. It centers around a real-world testcase--involving a treatment for hypertension after open heartsurgery--and explains how to use Bayesian methods to accommodateboth ethical and scientific imperatives. The book grew out of the direct involvement in the project by adiverse group of experts in medicine, statistics, philosophy, andthe law. Not only do they contribute essays on the scientific,technological, legal, and ethical aspects of clinical trials, butthey also critique and debate each other's opinions, creating aninteresting, personalized text. Bayesian Methods and Ethics in a Clinical Trial Design* Answers commonly raised questions about Bayesian methods* Describes the advantages and disadvantages of this methodcompared with other methods* Applies current ethical theory to a particular class of designfor clinical trials* Discusses issues of informed consent and how to serve a patient'sbest interest while still obtaining uncontaminated scientific data* Shows how to use Bayesian probabilistic methods to createcomputer models from elicited prior opinions of medical experts onthe best treatment for a type of patient* Contains several chapters on the process, results, andcomputational aspects of the test case in question* Explores American law and the legal ramifications of using humansubjects For statisticians and biostatisticians, and for anyone involvedwith medicine and public health, this book provides both apractical guide and a unique perspective on the connection betweentechnological developments, human factors, and some of the largerethical issues of our times.

This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic of the collection is understanding how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the consequences of this turn for Bayesian statistics. There are four principal themes to the collection: cooperative, non-sequential decisions; the representation and measurement of 'partially ordered' preferences; non-cooperative, sequential decisions; and pooling rules and Bayesian dynamics for sets of probabilities. The volume will be particularly valuable to philosophers concerned with decision theory, probability, and statistics, statisticians, mathematicians, and economists.

This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic of the collection is understanding how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the consequences of this turn for Bayesian statistics. There are four principal themes to the collection: cooperative, non-sequential decisions; the representation and measurement of 'partially ordered' preferences; non-cooperative, sequential decisions; and pooling rules and Bayesian dynamics for sets of probabilities. The volume will be particularly valuable to philosophers concerned with decision theory, probability, and statistics, statisticians, mathematicians, and economists.

Praise for the first edition: Principles of Uncertaintyis a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. … the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. … A must-read for sure!—Christian Robert, CHANCEIt's a lovely book, one that I hope will be widely adopted as a course textbook.—Michael Jordan, University of California, Berkeley, USALike the prize-winning first edition, Principles of Uncertainty, Second Edition is an accessible, comprehensive text on the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples. It presents an introduction to the subjective Bayesian approach which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. This new edition has been updated throughout and features new material on Nonparametric Bayesian Methods, the Dirichlet distribution, a simple proof of the central limit theorem, and new problems.Key Features: First edition won the 2011 DeGroot Prize Well-written introduction to theory of Bayesian statistics Each of the introductory chapters begins by introducing one new concept or assumption Uses "just-in-time mathematics"—the introduction to mathematical ideas just before they are applied