General

Statistical Analysis of Human Growth and Development is an accessible and practical guide to a wide range of basic and advanced statistical methods that are useful for studying human growth and development. Designed for nonstatisticians and statisticians...

This book gives an introduction to the theoretical and computational fluid dynamics of a compressible fluid. It focuses on the basic assumptions and the formulation of the theory of compressible flow as well as on the methods of solving problems.About...

Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological...

Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed...

The first book to examine weakly stationary random fields and their connections with invariant subspaces (an area associated with functional analysis). It reviews current literature, presents central issues and most important results within the area. For...

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you...

State-of-the-Art Methods for Drug Safety AssessmentResponding to the increased scrutiny of drug safety in recent years, Quantitative Evaluation of Safety in Drug Development: Design, Analysis and Reporting explains design, monitoring, analysis, and...

Written specifically for biotechnology scientists, engineers, and quality professionals, this book describes and demonstrates the proper application of statistical methods throughout Chemistry, Manufacturing, and Controls (CMC). Filled with case studies,...

The normal distribution is widely known and used by scientists and engineers. However, there are many cases when the normal distribution is not appropriate, due to the data being skewed. Rather than leaving you to search through journal articles,...

This book reviews the state-of-the-art advances in skew-elliptical distributions and provides many new developments in a single volume, collecting theoretical results and applications previously scattered throughout the literature. The main goal of this...

Technological improvements continue to push back the frontier of processor speed in modern computers. Unfortunately, the computational intensity demanded by modern research problems grows even faster. Parallel computing has emerged as the most successful...

Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially...

Since 1945, "The Annual Deming Conference on Applied Statistics" has been an important event in the statistics profession. In Clinical Trial Biostatistics and Biopharmaceutical Applications, prominent speakers from past Deming conferences present novel...

Those who work in allied health professions and education aim to make people's lives better. Often, however, it is hard to know how effective this work has been: would change have occurred if there was no intervention? Is it possible we are doing more...

Preeminent Experts Update a Well-Respected BookTaking into account the regulatory and scientific developments that have occurred since the second edition, Design and Analysis of Bioavailability and Bioequivalence Studies, Third Edition provides a...

Using real data sets throughout, Survival Analysis in Medicine and Genetics introduces the latest methods for analyzing high-dimensional survival data. It provides thorough coverage of recent statistical developments in the medical and genetics fields...

Classroom tested and the result of over 30 years of teaching and research, this textbook is an invaluable tool for undergraduate and graduate data analysis courses in environmental sciences and engineering. It is also a useful reference on modern digital...

Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of...

An accessible book on sampling techniques with emphasis on and illustrations from surveys of human populations. Explains how to design and execute valid samples of moderate dimensions and difficulty, avoid selection biases and how to become more adept at...

A precise and accessible presentation of linear model theory, illustrated with data examples Statisticians often use linear models for data analysis and for developing new statistical methods. Most books on the subject have historically discussed...

There is a growing interest in developing register-based surveys; that is surveys based upon already available administrative data. Since huge amounts of such data are generated within various administrative systems, the opportunity exists to use the...

Item Response Theory clearly describes the most recently developed IRT models and furnishes detailed explanations of algorithms that can be used to estimate the item or ability parameters under various IRT models. Extensively revised and expanded, this...

Carefully designed for use by clinical and pharmaceutical researchers and scientists, Handbook of Regression Analysis and Modeling explores statistical methods that have been adapted into biological applications for the quickly evolving field of...

Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous...

By discussing statistical concepts in the context of transportation planning and operations, Transportation Statistics and Microsimulation provides the necessary background for making informed transportation-related decisions. It explains the why behind...

From Pythagoreans to Hegel, and beyond, this book gives a brief overview of the history of the notion of graphs and introduces the main concepts of graph theory in order to apply them to philosophy. In addition, this book presents how philosophers can...

Providing an interface between dry-bench bioinformaticians and wet-lab biologists, DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data, in...

Modern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more...

DNA evidence is widely used in the modern justice system. Statistical methodology plays a key role in ensuring that this evidence is collected, interpreted, analysed and presented correctly. This book is a guide to assessing DNA evidence and presenting...

Confidence Intervals for Discrete Data in Clinical Research is designed as a toolbox for biomedical researchers. Analysis of discrete data is one of the most used yet vexing areas in clinical research. The array of methodologies available in the...

Presents a useful new technique for analyzing the extreme-value behaviour of random fields Modern science typically involves the analysis of increasingly complex data. The extreme values that emerge in the statistical analysis of complex data are often...

A comprehensive and timely edition on an emerging new trend in time series Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA),...

This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling...

The past 10 years have brought amazing changes to the technologies used to turn remotely sensed data into maps. As a result, the principles and practices necessary for assessing the accuracy of those maps have also evolved and matured. This third edition...

This book describes a systematic methodology for formulating mixed-ingredient products so that they perform to particular standards, providing scientists and engineers with a fast track to the implementation of the methodology. Examples from a wide...

Probability with STEM Applications, Third Edition, is an accessible and well-balanced introduction to post-calculus applied probability. Integrating foundational mathematical theory and the application of probability in the real world, this leading...

Advances in Shannon's Sampling Theory provides an up-to-date discussion of sampling theory, emphasizing the interaction between sampling theory and other branches of mathematical analysis, including the theory of boundary-value problems, frames,...

The growth of the pharmaceutical industry over the past decade is astounding, but the impact of this growth on statistics is somewhat confusing. While software has made analysis easier and more efficient, regulatory bodies now demand deeper and more...

Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored...

Past, Present, and Future of Statistical Science was commissioned in 2013 by the Committee of Presidents of Statistical Societies (COPSS) to celebrate its 50th anniversary and the International Year of Statistics. COPSS consists of five charter member...