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Data Modeling for Metrology and Testing in Measurement Science

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Cover of 'Data Modeling for Metrology and Testing in Measurement Science'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Data Modeling Principles in Metrology and Testing
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    Chapter 2 Probability in Metrology
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    Chapter 3 Three Statistical Paradigms for the Assessment and Interpretation of Measurement Uncertainty
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    Chapter 4 Interval Computations and Interval-Related Statistical Techniques: Tools for Estimating Uncertainty of the Results of Data Processing and Indirect Measurements
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    Chapter 5 Parameter Estimation Based on Least Squares Methods
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    Chapter 6 Frequency and Time—Frequency Domain Analysis Tools in Measurement
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    Chapter 7 Data Fusion, Decision-Making, and Risk Analysis: Mathematical Tools and Techniques
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    Chapter 8 Comparing Results of Chemical Measurements: Some Basic Questions from Practice
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    Chapter 9 Modelling of Measurements, System Theory and Uncertainty Evaluation
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    Chapter 10 Approaches to Data Assessment and Uncertainty Estimation in Testing
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    Chapter 11 Monte Carlo Modeling of Randomness
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    Chapter 12 Software Validation and Preventive Software Quality Assurance for Metrology
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    Chapter 13 Virtual Istrumentation
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    Chapter 14 Internet-Enabled Metrology
Attention for Chapter 7: Data Fusion, Decision-Making, and Risk Analysis: Mathematical Tools and Techniques
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Citations

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Chapter title
Data Fusion, Decision-Making, and Risk Analysis: Mathematical Tools and Techniques
Chapter number 7
Book title
Data Modeling for Metrology and Testing in Measurement Science
Published by
Birkhäuser Boston, January 2009
DOI 10.1007/978-0-8176-4804-6_7
Book ISBNs
978-0-8176-4592-2, 978-0-8176-4804-6
Authors

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

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Professor 1 25%
Unknown 1 25%
Readers by discipline Count As %
Engineering 2 50%
Social Sciences 1 25%
Unknown 1 25%

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