Titlebook: Data Modeling for Metrology and Testing in Measurement Science; Franco Pavese,Alistair B. Forbes Book 2009 Birkhäuser Boston 2009 Internet

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2164-3679 of fields, including chemistry, software engineering, and mThe 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

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The Cognitive and Behavioural Sciencesmena or process. This chapter deals with the different types of description of the uncertainty components, with a wide selection of citations from reference international documents, and then with the different models corresponding to the different data characteristics. An extended bibliography is included.

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https://doi.org/10.1007/978-0-387-77632-3ual instruments and with the different forms of their implementation. Both the hardware and software components of a virtual instruments are detailed. A short reference to virtual laboratories is also included.

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Probability in Metrology,ecent results that make a systematic use of probability an appropriate logic for measurement. It is suggested that these two mainstreams may ultimately converge in a unique theory of measurement, formulated in a probabilistic language and applicable to all domains of science.

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,Frequency and Time—Frequency Domain Analysis Tools in Measurement,pace or time localization of short-lived repeating patterns. These are signal-processing tools which require some good understanding of the underlying theory to avoid common pitfalls and circumvent some limitations. Examples are given to show applicability.