Pavese / Forbes Data Modeling for Metrology and Testing in Measurement Science

1. Auflage 2008
ISBN: 978-0-8176-4804-6
Verlag: Birkhäuser Boston
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 486 Seiten, Web PDF

Reihe: Mathematics and Statistics (R0)

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

Data Modeling for Metrology and Testing in Measurement Science may be used as a textbook in graduate courses on data modeling and computational methods, or as a training manual in the fields of calibration and testing. The book will also serve as an excellent reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement science.

Zielgruppe

Research

Autoren/Hrsg.

Pavese, Franco

Forbes, Alistair B.

Inhaltsverzeichnis

An Introduction to Data Modeling Principles in Metrology and Testing.- Probability in Metrology.- Three Statistical Paradigms for the Assessment and Interpretation of Measurement Uncertainty.- Interval Computations and Interval-Related Statistical Techniques: Tools for Estimating Uncertainty of the Results of Data Processing and Indirect Measurements.- Parameter Estimation Based on Least Squares Methods.- Frequency and Time#x2014;Frequency Domain Analysis Tools in Measurement.- Data Fusion, Decision-Making, and Risk Analysis: Mathematical Tools and Techniques.- Comparing Results of Chemical Measurements: Some Basic Questions from Practice.- Modelling of Measurements, System Theory and Uncertainty Evaluation.- Approaches to Data Assessment and Uncertainty Estimation in Testing.- Monte Carlo Modeling of Randomness.- Software Validation and Preventive Software Quality Assurance for Metrology.- Virtual Istrumentation.- Internet-Enabled Metrology.