Subir Ghosh – författare

"Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian, bootstrap, adaptive, univariate, and multivariate statistical methods, as well as practical uses of Markov chain models."

Explains the role of statistics in improving the quality of collecting and analyzing information for a wide variety of applications. The book examines the function of statisticians in quality improvement. It discusses statistical process control, quality statistical tables, and quality and warranty; quality standards in medicine and public health; Taguchi robust designs and survival models; and more.

"Describes recent developments and surveys important topics in the areas of multivariate analysis, design of experiments, and survey sampling. Features the work of nearly 50 international leaders."

"Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian, bootstrap, adaptive, univariate, and multivariate statistical methods, as well as practical uses of Markov chain models."

"Describes recent developments and surveys important topics in the areas of multivariate analysis, design of experiments, and survey sampling. Features the work of nearly 50 international leaders."

Explains the role of statistics in improving the quality of collecting and analyzing information for a wide variety of applications. The book examines the function of statisticians in quality improvement. It discusses statistical process control, quality statistical tables, and quality and warranty; quality standards in medicine and public health; Taguchi robust designs and survival models; and more.

Explore the foundations of, and cutting-edge developments in, statistics Statistical Planning and Inference: Concepts and Applications delivers a robust introduction to statistical planning and inference, including classical and computer age developments in statistical science. The book examines the challenges faced in statistical planning and inference, exploring the optimum methods identifying limitations and commonly encountered pitfalls. It addresses linear and non-linear statistical inference and discusses noise-effect reduction, error rates, balanced and unbalanced data, model selection, discrimination and classification, truncated and censored data, and experimental designs. Each chapter offers readers problems and solutions and illustrative examples to introduce the concepts and methods discussed within. The book offers: Analysis of both classical theory and modern developments in the field of statistical inference and planningExpansive discussions of linear and non-linear statistical inferenceStatistical problems and solutions to test the reader’s progress through and retention of the material contained withinAimed at practitioners and researchers in the field of statistics, Statistical Planning and Inference: Concepts and Applications is also a must-read resource for graduate students, professors, and researchers in the life sciences, agriculture, psychology, education and measurement, sociology, computer and engineering sciences, and all other fields that rely on statistical concepts.