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: Univariate normal distribution Non-normal distributions Univariate linear regression models Nonparametric tolerance intervals The one-way random model with balanced data The multivariate normal distribution The one-way random model with unbalanced data The multivariate linear regression model General mixed models Bayesian tolerance intervals 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: Classical and Bayesian
This work offers an approach to quality control that relies on statistical tolerance regions, and discusses computer graphic analysis highlighting multivariate profile charts.
Presents a detailed exposition of statistical intervals and emphasizes applications in industry.
In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.
The book is a collection of some of the research presented at the workshop of the same name held in May 2003 at Rutgers University.
r. The case study in Section 18.1 shows how to construct, and contrasts, likelihood, bootstrap, and Wald-approximation confidence intervals on the proportion of defective integrated circuits from a manufacturing process, ...
Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings.
Written by one of the foremost authorities in the field, Mechanical Tolerance Stackup and Analysis presents proven and easy-to-use methods for determining whether selected dimensioning and tolerancing schemes will yield functional parts and ...
Designed specifically for the non-statistician, this valuable guide focuses on the practical problems of the field researcher.
Tolerance Design of Electronic Circuits presents an account of design and analysis methods used to minimize the unwanted effects of component tolerances.Highlights of the book include• An overview of the concepts of Tolerance Analysis and ...