Data Modeling for Metrology and Testing in Measurement Science [Hardcover]

This book?provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods and focusing on techniques with?a broad range of real-world applications.

The book will be useful as a textbook?for graduate students, or as a training manual in the fields of calibration and testing. The work may also serve as a?reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement?science.

This book provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods described in standard texts. The main focus is on techniques having a broad range of real-world applications.

The aim of this book is to provide, ?rstly, an introduction to probability and statistics especially directed to the metrology and testing ?elds and secondly, a comprehensive, newer set of modelling methods for data and uncertainty analysis that are generally not considered yet within mainstream methods. The book brings, for the ?rst time, a coherent account of these newer me- ods and their computational implementation. They are potentially important because they address problems in application ?elds where the usual hypot- ses that are at the basis of most of the traditional statistical and probabilistic methods, for example, relating to normality of the probability distributions, are frequently not ful?lled to such an extent that an accurate treatment of the calibration or test data using standard approaches is not possible. Additi- ally, the methods can represent alternative ways of data analysis, allowing a deeper understanding of complex situations in measurement. The book lends itself as a possible textbook for undergraduate or postgraduate study in an area where existing texts focus mainly on the most common and well-known methods that do not encompass l£Ù