Books in the Wiley Series in Probability and Statistics series

The Construction of Optimal Stated Choice Experiments provides an accessible introduction to the construction methods needed to create the best possible designs for use in modeling decision-making. It uniquely covers disciplines from marketing to transportation, environmental resource economics to public welfare analysis.

Bayesian methods combine information available from data with any prior information available from expert knowledge. The Bayes linear approach follows this path, offering a quantitative structure for expressing beliefs, and systematic methods for adjusting these beliefs, given observational data.

This book covers the most common methods for analyzing single, double, three-way and multi-way data. Geared towards applications and the decisions that have to be made to get meaningful analyses, it presents a variety of models illustrated using commercially available software.

This book is a practical guide for experimenters who are faced with selecting optimal treatments based on empirical studies.

Reliability & Risk: A Bayesian Perspective addresses the need for a sound introduction to the mathematical and statistical aspects of reliability analysis from a Bayesian perspective. It features many real examples, taken from the author's vast experience, and lots of applications from reliability engineering.

This book explores data management from study development to final analysis and suggests alternative approaches, with guidelines on optimal approaches under various circumstances. It contains discussions of the various approaches to clinical trials for some of the major diseases. This second edition compares approaches in the U.S.

Mathematical models are used to simulate complex real-world phenomena in many areas of science and technology. Large complex models typically require inputs whose values are not known with certainty.

A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics.

The purpose of this book is to introduce the theory of U-Statistics and illustrate it with a wide range of timely applications arising in genetics, biomedical, and psychological research.

Not even the most brilliant statistician can instantly recall every rule and concept that forms the daily bread of statistical work. Sensibly organized for quick reference, Statistical Rules of Thumb, Second Edition compiles simple rules that are widely applicable, robust, and elegant, and that capture key statistical concepts.

Fuzzy logic provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy, or missing input information. Statistical Methods for Fuzzy Data deftly explains the basics of fuzzy logic and the use of statistical methods for fuzzy data sets.

* First book on robust techniques to be specifically aimed at biostatistics. * Supported by an accompanying website containing data sets, programs written in R and a user guide.

Multivariable regression models are of fundamental importance in all areas of science in which empirical data must be analyzed. This book proposes a systematic approach to building such models based on standard principles of statistical modeling.

This book fills this gap, providing a comprehensive, self-contained introduction to regression modeling used in the analysis of time-to-event data in epidemiological, biostatistical, and other health-related research.

This book represents a serious approach to the study of linear models and their applications through discussion of analysis of variance (ANOVA) techniques. Throughout the book there is an equal emphasis on orthogonal representations that delve from the history of the subject and on the vector-matrix approach that has surfaced in recent years.

This comprehensive resource provides the algorithmic methods and state-of-the-art tools to successfully visualize statistical data. The coverage offers insight into underlying processes of density estimation, emphasizing use of visualization tools rather than only the theoretical concepts of classification and regression.

Praise for the First Edition "This book... is a significant addition to the literature on statistical practice... should be of considerable interest to those interested in these topics.

A modern and comprehensive treatment of tolerance intervals and regions The topic of tolerance intervals and tolerance regions has undergone significant growth during recent years, with applications arising in various areas such as quality control, industry, and environmental monitoring.

The chapters of this book are from the recent writings of George E.P. Box, an acknowledged world leader in the application and theory of quality methodology to management, process improvement, process design, and discovery. Box's unique ability to explain complex ideas simply and appealingly with wit and cogent illustration is well known.

This book provides a balanced coverage of underlying theory of statistical analysis of designed experiments and its numerous applications. Data sets from real life studies are used throughout, and graphical as well as formal analyses are illustrated using MINITAB(c) software.

Praise for the First Edition "This book . . . is a significant addition to the literature on statistical practice . . . should be of considerable interest to those interested in these topics."--International Journal of Forecasting Recent research has shown that monitoring techniques alone are inadequate for modern Statistical Process Control (SPC), and there exists a need for these techniques to be augmented by methods that indicate when occasional process adjustment is necessary. Statistical Control by Monitoring and Adjustment, Second Edition presents the relationship among these concepts and elementary ideas from Engineering Process Control (EPC), demonstrating how the powerful synergistic association between SPC and EPC can solve numerous problems that are frequently encountered in process monitoring and adjustment. The book begins with a discussion of SPC as it was originally conceived by Dr. Walter Shewart and Dr. W. Edwards Deming. Subsequent chapters outline the basics of the new integration of SPC and EPC, which is not available in other related books. Thorough coverage of time series analysis for forecasting, process dynamics, and non-stationary models is also provided, and these sections have been carefully written so as to require only an elementary understanding of mathematics. Extensive graphical explanations and computational tables accompany the numerous examples that are provided throughout each chapter, and a helpful selection of problems and solutions further facilitates understanding. Statistical Control by Monitoring and Adjustment, Second Edition is an excellent book for courses on applied statistics and industrial engineering at the upper-undergraduate and graduate levels. It also serves as a valuable reference for statisticians and quality control practitioners working in industry.

Methods of subjective statistical analysis have seen a resurgence of activity in the last decade. This book treats the theory of probability and the logic of uncertainty in a systematic way. It features a technical presentation of the mathematical impact of personal beliefs and values on statistical analysis.

Serving as a text for a two semester sequence on probability and statistical inference complex Models for Probability and Statistical Inference: Theory and Applications features exercises throughout the book and selected answers (not solutions). Each section is followed by a selection of problems, from simple to more complex.

This book provides a comprehensive treatment of the design of split-plot and blocked experiments, two types of experiments that are extremely popular in practice.

This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real--world examples which do not feature in many standard texts.

The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike.

Explores the major topics in Monte Carlo simulation. This title features the information that facilitates an understanding of problem solving across a wide array of subject areas, such as engineering, mathematics, and the physical and life sciences. It introduces the basic concepts of probability, Markov processes, and convex optimization.

This Set Contains:Continuous Multivariate Distributions, Volume 1, Models and Applications, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson; Continuous Univariate Distributions, Volume 1, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson; Continuous Univariate Distributions, Volume 2, 2nd Edition by Samuel Kotz, N.

This set includes Design and Analysis of Experiments, Volume 1, Introduction to Experimental Design, 2nd Edition & Design and Analysis of Experiments, Volume 2, Advanced Experimental Design. Design and Analysis of Experiments, Volume 1, Second Edition provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments and also details the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book further addresses the needs of practitioners and successfully provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions.Design and Analysis of Experiments, Volume 2: Advanced Experimental Design is the second of a two-volume body of work that builds upon the philosophical foundations of experimental design set forth half a century ago by Oscar Kempthorne, and features the latest developments in the field.