Books in the Wiley Series in Probability and Statistics series

From its initial publication this book has been the standard text on the subject. Since then there has been a continuing high level of activity, and work has developed in all major areas. This third edition reflects the latest state of knowledge with fully revised and extended coverage of all topics.

The concepts of epidemiology, the science that uses statistical methods to investigate associations between risk factors and disease outcomes in human populations, are developed using examples involving real data from published studies.

The classic text for understanding complex statistical probability An Introduction to Probability Theory and Its Applications offers comprehensive explanations to complex statistical problems. Delving deep into densities and distributions while relating critical formulas, processes and approaches, this rigorous text provides a solid grounding in probability with practice problems throughout. Heavy on application without sacrificing theory, the discussion takes the time to explain difficult topics and how to use them. This new second edition includes new material related to the substitution of probabilistic arguments for combinatorial artifices as well as new sections on branching processes, Markov chains, and the DeMoivre-Laplace theorem.

Regression analysis is the study of the dependence of a response variable on one or more predictor variables. It is among the most widely used methods in statistics. In recent years, several new ways to approach regression have been presented.

A Classic adapted to modern times Rewritten and updated, this new edition of Statistics for Experimenters adopts the same approaches as the landmark First Edition by teaching with examples, readily understood graphics, and the appropriate use of computers.

Considerable changes have occurred in the field of order statistics in the nearly 20 years since "Order Statistics", second edition was published. This third edition gives a helpful account of order statistics, useful to students as well as those needing a guide to the extensive literature.

This highly-regarded text serves as a quick reference book which offers clear, concise instructions on how and when to use the most popular nonparametric procedures.

In recent years there has been a growing interest in the application of the mathematical functions known as wavelets to a broad range of statistical problems. This pioneering, state-of-the-art book focuses on those applications.

Statistics have helped shape every area of science. Without the means to analyze critical data, none of the great disoveries of the past would be possible. This paperback reprint of a Wiley bestseller shows the development of these data analysis tools and the manner in which they aided technological development prior to 1750.

Presents methods for the design and analysis of surveys, studies, and experiments when the data is qualitative and categorical. This work also covers the delta methods for multinomial frequencies. It discusses topics in misclassification and in reliability assessment.

Serving as a "bridge" to prepare social scientists and students for professional-level use of statistics, this volume outlines the main numerical estimations issues along with various means of avoiding specific common pitfalls.

Gives a treatment of data oriented techniques as well as classical methods. This sourcebook emphasizes principles rather than mathematical detail, and the coverage ranges from the practical problems of graphically representing high dimensional data to the theoretical problems relating to matrices of random variables.

This book is the first of two volumes that update Oscar Kempthorne's groundbreaking 1952 classic of the same name. This first volume is concerned primarily with the philosophical basis for experimental design and a mathematical-statistical framework within which to discuss the subject.

Converted into a paperback format, at a reduced price Markov Processes: Characterization and Convergence is ideal as a graduate text and/or reference on Markov Processes and their relationship to operator semigroups.

This book provides statistical methods and models that can be used to produce short-term forecasts. The authors provide an intermediate-level discussion of a variety of statistical forecasting methods and models, to explain their interconnections, and to bridge the gap between theory and practice. .

This book explores the martingale approach to the statistical analysis of counting processes, with an emphasis on application of those methods to censored failure time data. Introduced in the 1970s, this approach has proven to be remarkably successful in yielding results about statistical methods for many problems arising in censored data.

An accessible, clearly organized survey of the basic topics of measure theory for students and researchers in mathematics, statistics, and physics In order to fully understand and appreciate advanced probability, analysis, and advanced mathematical statistics, a rudimentary knowledge of measure theory and like subjects must first be obtained.

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 volume presents a detailed description of the statistical distributions that are commonly applied to such fields as engineering, business, economics and the behavioural, biological and environmental sciences.

Presents the first comprehensive guide to the analysis of spatial data. Each chapter covers a particular data format and the associated class of problems, introducing theory, giving computational suggestions, and providing examples. Methods are illustrated by computer-drawn figures.

This volume is written on the subject of the summarizing of the variability of statistical data known as the analysis of variance table. Penned in a readable style, it provides an up-to-date treatment of research in the area.

Dealing with the "how to do it" as well as the '"why it works," this book is designed for practitioners of principal component analysis. It explores topics such as: extension to p variables, scaling input data, inferential procedures, operations with group data, and vector interpretation.

A unique approach illustrating discrete distribution theory through combinatorial methods This book provides a unique approach by presenting combinatorial methods in tandem with discrete distribution theory. This method, particular to discreteness, allows readers to gain a deeper understanding of theory by using applications to solve problems.

Bayesian Statistical Modelling, Second Edition, provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets.

This valuable book-length treatment of the field offers coverage of estimation for situations where the model variables are observed subject to measurement error. Included are regression models with errors in the variables, latent variable models, and factor models.

This book provides a lucid and comprehensive introduction to simulation methods, and features examples and applications using Maple. Maple is widely used at undergraduate mathematics level in the UK, US and Europe. It is readily available to students, researchers and practitioners, and the code is easily transferrable into other languages.

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation.

This newly available and affordably priced paperback version of Exploring Data Tables, Trends, and Shapes presents major advances in exploratory data analysis and robust regression methods and explains the techniques, relating them to classical methods.

Discover how to optimize business strategies from both qualitative and quantitative points of view Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk.