A modern and comprehensive treatment of tolerance intervals and regions The topic of tolerance intervals and tolerance regions has undergone significant growth during recent years, with applications arising in various areas such as quality control, industry, and environmental monitoring. Statistical Tolerance Regions presents the theoretical development of tolerance intervals and tolerance regions through computational algorithms and the illustration of numerous practical uses and examples. This is the first book of its kind to successfully balance theory and practice, providing a state-of-the-art treatment on tolerance intervals and tolerance regions. The book begins with the key definitions, concepts, and technical results that are essential for deriving tolerance intervals and tolerance regions. Subsequent chapters provide in-depth coverage of key topics including: <ul>
<li>Univariate normal distribution</li> <li>Non-normal distributions</li> <li>Univariate linear regression models</li> <li>Nonparametric tolerance intervals</li> <li>The one-way random model with balanced data</li> <li>The multivariate normal distribution</li> <li>The one-way random model with unbalanced data</li> <li>The multivariate linear regression model</li> <li>General mixed models</li> <li>Bayesian tolerance intervals</li> </ul>
A final chapter contains coverage of miscellaneous topics including tolerance limits for a ratio of normal random variables, sample size determination, reference limits and coverage intervals, tolerance intervals for binomial and Poisson distributions, and tolerance intervals based on censored samples. Theoretical explanations are accompanied by computational algorithms that can be easily replicated by readers, and each chapter contains exercise sets for reinforcement of the presented material. Detailed appendices provide additional data sets and extensive tables of univariate and multivariate tolerance factors. Statistical Tolerance Regions is an ideal book for courses on tolerance intervals at the graduate level. It is also a valuable reference and resource for applied statisticians, researchers, and practitioners in industry and pharmaceutical companies.

Statistical Tolerance Regions: Theory, Applications, and Computation

Science & Math

Mathew, Thomas

Krishnamoorthy, Kalimuthu

Mathematics

wiley

An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models at an advanced level. Statistical Tests for Mixed Linear Models: <ul>
<li>Combines analysis and testing in one self-contained volume.</li> <li>Describes analysis of variance (ANOVA) procedures in balanced and unbalanced data situations.</li> <li>Examines methods for determining the effect of imbalance on data analysis.</li> <li>Explains exact and optimum tests and methods for their derivation.</li> <li>Summarizes test procedures for multivariate mixed and random models.</li> <li>Enables novice readers to skip the derivations and discussions on optimum tests. Offers plentiful examples and exercises, many of which are numerical in flavor.
</li> <li>Provides solutions to selected exercises.</li> </ul>
Statistical Tests for Mixed Linear Models is an accessible reference for researchers in analysis of variance, experimental design, variance component analysis, and linear mixed models. It is also an important text for graduate students interested in mixed models.

Statistical Tests for Mixed Linear Models (Wiley Series in Probability and Statistics)

Khuri, André I.

Sinha, Bimal K.

Wiley-Interscience

Designed for individuals in the enterprise resource planning (ERP) field, this business resource presents the main concepts of integrated packaged software systems that are used in order management in many large companies. Managers will benefit from the information on improving e-business integration and supply chain management. This guide offers the fundamentals of logistical management and prepares those new to the field for the EC-Council ERP exam.

Enterprise Resource Planning

Computers & Technology

Osb Pub Pte Ltd

Key information on the use of business intelligence (BI) decision-support applications is presented in this guide to implementing BI projects and improving project cycles. Offered are detailed instructions on avoiding the factors that lead to the failure of BI, staying ahead of business competitors, and increasing product market shares. Senior executives, students of the EC-Council BI exam, and business professionals will benefit from these detailed explanations of the tools BI offers.

Business Intelligence

The Awareness of Food as Medicine: Live a long, healthy, happy, & satisfied life

Health, Fitness & Dieting

Diets & Weight Loss

Self-Publish

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