Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Principles of Uncertainty
Praise for the first edition: Principles of Uncertainty is 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, CHANCE It's a lovely book, one that I hope will be widely adopted as a course textbook. —Michael Jordan, University of California, Berkeley, USA Like 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 i...
Statistics in the Law
Introduction: Deciding Whether to be an Expert Witness 6. Part 1. What's it like to be an Expert Witness? 9. Introduction. A: Pioneers. 1. Damned Liars and Expert Witnesses Paul Meier. 2. Statisticians, Econometricians, and Adversary Proceedings Franklin M. Fisher. B A Very Brief Introduction to U.S. Law, and to the Role of Expert Witnesses. C Qualifications and Responsibilities of the Expert Witness 33. 1. Epidemiologic Evidence in the Silicone Breast Implant Cases Michael O. Finkelstein and Bruce Levin. 2. Frye v. United States. 3. Daubert v. Merrell Dow Pharmaceuticals. 4. Kumho Tire Co. v.
Rethinking the Foundations of Statistics
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.
A Probabilistic Analysis of the Sacco and Vanzetti Evidence
A Probabilistic Analysis of the Sacco and Vanzetti Evidence is aBayesian analysis of the trial and post-trial evidence in the Saccoand Vanzetti case, based on subjectively determined probabilitiesand assumed relationships among evidential events. It applies theideas of charting evidence and probabilistic assessment to thiscase, which is perhaps the ranking cause celebre in all of Americanlegal history. Modern computation methods applied to inferencenetworks are used to show how the inferential force of evidence ina complicated case can be graded. The authors employ probabilisticassessment to obtain opinions about how influential each group ofevidential items is in reaching a conclusion about...
Pragmatics of Uncertainty
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.
Time Series
Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian t
Causation, Prediction, and Search
This book is intended for anyone, regardless of discipline, who is interested in the use of statistical methods to help obtain scientific explanations or to predict the outcomes of actions, experiments or policies. Much of G. Udny Yule's work illustrates a vision of statistics whose goal is to investigate when and how causal influences may be reliably inferred, and their comparative strengths estimated, from statistical samples. Yule's enterprise has been largely replaced by Ronald Fisher's conception, in which there is a fundamental cleavage between experimental and non experimental inquiry, and statistics is largely unable to aid in causal inference without randomized experimental trials. ...
An Introduction to Categorical Data Analysis
A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, ...
Loss Models
An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, ...
