General

"An understanding of the relationship between the product and the process in election polling is often lost. This edited volume unites ideas and researchers, with quality playing the central role." -J. Michael Brick, PhD, Director of the Survey...

A practical approach to the mathematical tools needed to increase portfolio growth, learn successful trading strategies, and manage the risks associated with market fluctuation Mathematical Asset Management presents an accessible and practical...

This book offers a predominantly theoretical coverage of statistical prediction, with some potential applications discussed, when data and/ or parameters belong to a large or infinite dimensional space. It develops the theory of statistical prediction,...

The promotion of standards and guidelines to advance quality assurance and control is an integral part of the health care sector. Quantitative methods are needed to monitor, control and improve the quality of medical processes. Statistical Development of...

Info-metrics is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is at the intersection of information theory, statistical inference, and decision-making under uncertainty. It plays an...

Nowadays bioinformaticians and geneticists are faced with myriad high-throughput data usually presenting the characteristics of uncertainty, high dimensionality and large complexity. These data will only allow insights into this wealth of so-called...

The Valencia International Meetings on Bayesian Statistics, held every four years, provide the forum for researchers to come together to present and discuss frontier developments in the field. The resulting Proceedings provide a definitive, up-to-date...

Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the...

BASIC STATISTICS FOR THE BEHAVIORAL SCIENCES, International Edition demystifies and fully explains statistics without leaving out relevant topics or simply presenting formulas, in a format that is non-threatening and inviting to students. The author's...

Professor Cramer, author of the pivotal Mathematical Methods of Statistics (1946), examines problems in the theory of stochastic processes that can be considered as generalizations of problems in the classical theory of statistical inference. He...

Encompassing both introductory and more advanced research material, these notes deal with the author's contributions to stochastic processes and focus on Brownian motion processes and its derivative white noise. Originally published in 1970. The...

In this calculus-based text, theory is developed to a practical degree around models used in real-world applications. Proofs of theorems and "tricky" probability calculations are minimized. Computing and simulation are introduced to make more difficult...

This text employs the latest ideas in teaching business statistics and follows the philosophy espoused at the conference "Making Statistics More Effective in Schools of Business" (MSMESB). It emphasizes modern statistical methods and data...

Using a successfully class-tested approach that gives coherence to a broad range of introductory topics, this innovative text provides students with a big picture view of statistics as well as problem-solving strategies that can be applied to the...

By far the best-selling introduction to statistics for students in the behavioral and social sciences, this text continues to offer straightforward instruction, accuracy, built-in learning aids, and real-world examples. The goal of STATISTICS FOR THE...

Spreadsheet-based introduction to mathematical programming concepts and applications, intended for undergraduate and graduate students in management and engineering. Its emphasis on model building and its focus on formulation principles are key features...

Statistics for International Social Work And Other Behavioral Sciences presents statistics using straightforward, accessible language, making it easier for students of all backgrounds - particularly social work student undergraduates, graduates and...

Designed to help you overcome your apprehension about statistics, UNDERSTANDING BASIC STATISTICS, ENHANCED, 7E, INTERNATIONAL METRIC EDITION provides plenty of guidance and informal advice as it demonstrates the links between statistics and the real...

Nonlinear Time Series Analysis with R provides a practical guide to emerging empirical techniques allowing practitioners to diagnose whether highly fluctuating and random appearing data are most likely driven by random or deterministic dynamic forces. It...

This advanced text focuses on the uses of distance sampling to estimate the density and abundance of biological populations. It addresses new methodologies, new technologies and recent developments in statistical theory and is the follow up companion to...

A collection of a wide range of research papers on applications of statistics to various sports from journals published by the American Statistical Association and the Royal Statistical Society from 2000 through 2004. The anthology is divided into eight...

Interrupted Time Series Analysis develops a comprehensive set of models and methods for drawing causal inferences from time series. It provides example analyses of social, behavioral, and biomedical time series to illustrate a general strategy for...

An accessible and engaging introduction to the study of probability and statistics Utilizing entertaining real-world examples, A Probability and Statistics Companion provides aunique, interesting, and accessible introduction to probability and...

Analyzing Baseball Data with R Second Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the...

Probability and Conditional Expectations bridges the gap between books on probability theory and statistics by providing the probabilistic concepts estimated and tested in analysis of variance, regression analysis, factor analysis, structural equation...

Uniquely reflects an engineering view to social systems in a wide variety of contexts of application Social Systems Engineering: The Design of Complexity brings together a wide variety of application approaches to social systems from an engineering...

A comprehensive and accessible introduction to modern quantitative risk management. The business world is rife with risk and uncertainty, and risk management is a vitally important topic for managers. The best way to achieve a clear understanding of risk...

In nonparametric and high-dimensional statistical models, the classical Gauss-Fisher-Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in...

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic...

Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction to the subject by first developing the theory of Markov processes in an elementary discrete time, finite state...

Branching Brownian motion (BBM) is a classical object in probability theory with deep connections to partial differential equations. This book highlights the connection to classical extreme value theory and to the theory of mean-field spin glasses in...

Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data. Many practitioners work with data that fail the assumptions of the common linear regression models, necessitating...

Thanks to the driving forces of the Ito calculus and the Malliavin calculus, stochastic analysis has expanded into numerous fields including partial differential equations, physics, and mathematical finance. This book is a compact, graduate-level text...

This book presents the latest numerical solutions to initial value problems and boundary value problems described by ODEs and PDEs. The author offers practical methods that can be adapted to solve wide ranges of problems and illustrates them in the...

Interest in the skew-normal and related families of distributions has grown enormously over recent years, as theory has advanced, challenges of data have grown, and computational tools have made substantial progress. This comprehensive treatment,...

The analysis of means (ANOM) is a graphical procedure used to quantify differences among treatment groups in a variety of experimental design and observational study situations. The ANOM decision chart allows one to easily draw conclusions and interpret...

Survival data consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. In contrast, many applications involve repeated-events data, where a unit may accumulate any number of events over time...

Readers will find this book an invaluable reference on the design of experiments. It contains hard-to-find information on topics such as change-over designs with residual effects and early treatment of analysis of covariance. Other topics include linear...

A discussion of some topics in the theory of large deviations such as moment-generating functions and Chernoff's theorem, and of aspects of estimation and testing in large samples, such as exact slopes of test statistics.Book InformationISBN...

This up-to-date account of algebraic statistics and information geometry explores the emerging connections between the two disciplines, demonstrating how they can be used in design of experiments and how they benefit our understanding of statistical...