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. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. ". . .Variance Components is an excellent book. It is organized and well written, and provides many references to a variety of topics. I recommend it to anyone with interest in linear models." —Journal of the American Statistical Association "This book provides a broad coverage of methods for estimating variance components which appeal to students and research workers . . . The authors make an outstanding contribution to teaching and research in the field of variance component estimation." —Mathematical Reviews "The authors have done an excellent job in collecting materials on a broad range of topics. Readers will indeed gain from using this book . . . I must say that the authors have done a commendable job in their scholarly presentation." —Technometrics This book focuses on summarizing 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. The book begins with the history of analysis of variance and continues with discussions of balanced data, analysis of variance for unbalanced data, predictions of random variables, hierarchical models and Bayesian estimation, binary and discrete data, and the dispersion mean model.

The book is based on both authors' several years of experience in teaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and offers a selection of classical and modern algebraic results that are useful in research work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results about the definiteness of matrices, especially for the differences of matrices, which enable superiority comparisons of two biased estimates to be made for the first time. We have attempted to provide a unified theory of inference from linear models with minimal assumptions. Besides the usual least-squares theory, alternative methods of estimation and testing based on convex loss func tions and general estimating equations are discussed. Special emphasis is given to sensitivity analysis and model selection. A special chapter is devoted to the analysis of categorical data based on logit, loglinear, and logistic regression models. The material covered, theoretical discussion, and its practical applica tions will be useful not only to students but also to researchers and con sultants in statistics.

Satellite Gravimetry and the Solid Earth: Mathematical Foundations presents the theories behind satellite gravimetry data and their connections to solid Earth. It covers the theory of satellite gravimetry and data analysis, presenting it in a way that is accessible across geophysical disciplines. Through a discussion of satellite measurements and the mathematical concepts behind them, the book shows how various satellite measurements, such as satellite orbit, acceleration, vector gravimetry, gravity gradiometry, and integral energy methods can contribute to an understanding of the gravity field and solid Earth geophysics. Bridging the gap between geodesy and geophysics, this book is a valuable resource for researchers and students studying gravity, gravimetry and a variety of geophysical and Earth Science fields. - Presents mathematical concepts in a pedagogic and straightforward way to enhance understanding across disciplines - Explains how a variety of satellite data can be used for gravity field determination and other geophysical applications - Covers a number of problems related to gravimetry and the gravity field, as well as the effects of atmospheric and topographic factors on the data - Addresses the regularization method for solving integral equations, isostasy based on gravimetric and flexure methods, elastic thickness, and sub-lithospheric stress

Instructs readers on how to use methods of statistics and experimental design with R software Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong theoretical background, but it is practically oriented to develop one's ability to tackle new and non-standard problems confidently. Taking a practical approach to applied statistics, this user-friendly guide teaches readers how to use methods of statistics and experimental design without going deep into the theory. Applied Statistics: Theory and Problem Solutions with R includes chapters that cover R package sampling procedures, analysis of variance, point estimation, and more. It follows on the heels of Rasch and Schott's Mathematical Statistics via that book's theoretical background—taking the lessons learned from there to another level with this book’s addition of instructions on how to employ the methods using R. But there are two important chapters not mentioned in the theoretical back ground as Generalised Linear Models and Spatial Statistics. Offers a practical over theoretical approach to the subject of applied statistics Provides a pre-experimental as well as post-experimental approach to applied statistics Features classroom tested material Applicable to a wide range of people working in experimental design and all empirical sciences Includes 300 different procedures with R and examples with R-programs for the analysis and for determining minimal experimental sizes Applied Statistics: Theory and Problem Solutions with R will appeal to experimenters, statisticians, mathematicians, and all scientists using statistical procedures in the natural sciences, medicine, and psychology amongst others.

Social Relations Modeling of Behavior in Dyads and Groups covers software, interpersonal perception (adult and children), the SRM with roles (e.g. in families), and applications to non-human research. Written in an accessible way, and for advanced undergraduates, graduate students and researchers, author Thomas E. Malloy strives to make inherently abstract material and unusual statistics understandable. As the social relations model provides a straightforward conceptual model of the components that make up behaviors in dyads and groups, this book will provide a powerful conceptual and methodological toolbox to analyze behaviors in dyads and groups across the sciences. This book is specifically designed to make this toolbox accessible - beyond interpersonal perception phenomena. It helps identify the relevant phenomena and dynamics surrounding behaviors in dyads and groups, and goes on to assess and analyze them empirically. - Captures essential conceptual and methodological topics around the scientific analyses of behaviors in groups and dyads - Situates the SRM in the history of dyadic research - Offers detailed guidance on research design and measurement operations - Organizes models and empirical results into easily read figures and tables - Demonstrates how SRM variances and covariances can be used as dependent measures in experiments - Conceptualizes novel phenomena in personality psychology using the SRM