Data Modeling for Metrology and Testing in Measurement Science

1. Front Matter

   Pages 1-17

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2. An Introduction to Data Modeling Principles in Metrology and Testing

   • Franco Pavese

   Pages 1-30

3. Probability in Metrology

   • Giovanni B. Rossi

   Pages 1-40

4. Three Statistical Paradigms for the Assessment and Interpretation of Measurement Uncertainty

   • William F. Guthrie, Hung-kung Liu, Andrew L. Rukhin, Blaza Toman, Jack C. M. Wang, Nien-fan Zhang

   Pages 1-45

5. Interval Computations and Interval-Related Statistical Techniques: Tools for Estimating Uncertainty of the Results of Data Processing and Indirect Measurements

   • Vladik Kreinovich

   Pages 1-29

6. Parameter Estimation Based on Least Squares Methods

   • Alistair B. Forbes

   Pages 1-30

7. Frequency and Time—Frequency Domain Analysis Tools in Measurement

   • Pedro M. Ramos, Raul C. Martins, Sergio Rapuano, Pasquale Daponte

   Pages 1-27

8. Data Fusion, Decision-Making, and Risk Analysis: Mathematical Tools and Techniques

   • Pedro S. Girão, Octavian Postolache, José M. D. Pereira

   Pages 1-50

9. Comparing Results of Chemical Measurements: Some Basic Questions from Practice

   • Paul De Bièvre

   Pages 1-19

10. Modelling of Measurements, System Theory and Uncertainty Evaluation

    • Klaus-D. Sommer

    Pages 1-23

11. Approaches to Data Assessment and Uncertainty Estimation in Testing

    • Wolfram Bremser, Werner Hässelbarth

    Pages 1-30

12. Monte Carlo Modeling of Randomness

    • Alan G. Steele, Robert J. Douglas

    Pages 1-41

13. Software Validation and Preventive Software Quality Assurance for Metrology

    • Norbert Greif, Dieter Richter

    Pages 1-41

14. Virtual Istrumentation

    • Octavian Postolache, Pedro S. Girão, José M.D. Pereira

    Pages 1-39

15. Internet-Enabled Metrology

    • Tanasko Tasić

    Pages 1-19

16. Back Matter

    Pages 1-18

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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 modern approaches to calibration and testing problems. The book is structured in such a way to guide readers with only a g- eral interest in measurement issues through a series of review papers, from an initial introduction to modelling principles in metrology and testing, to the basic principles of probability in metrology and statistical approaches to - certainty assessment.

• Internet
• Mathematica
• STATISTICA
• Wavelet
• calculus
• data analysis
• fuzzy
• metrology
• modeling
• probability
• quality
• quality assurance
• risk analysis
• systems theory
• uncertainty

From the reviews:

“This is a surprisingly eclectic compilation that I found full of interesting concepts and new knowledge. … Academic researchers and National Measurement Institutes will certainly recommend the text to their libraries. Their research students will benefit … .”­­­ (D. Brynn Hibbert, Accreditation and Quality Assurance, Vol. 15, 2010)

• Metrologica (INRIM), Divisione Termodinamica, Istituto Nazionale di Ricerca, Torino, Italy

  Franco Pavese

• MSC , Module 13 , National Physics Laboratory , Teddington, Middlesex, United Kingdom

  Alistair B. Forbes

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