Abstract
The aim of this chapter is to provide a simple measurement example and solve it according to the three different approaches covered in Sections 3.1 and 3.2. The authors are aware that the readers can probably understand only the standard statistical methods, widely and universally known, while the RFV approach, which at this point of the book has been only shortly recalled, will be not fully understood. Everything will be explained later in the book, and the readers should now simply trust the reported results, because the aim of this example is not to understand how these results have been obtained but simply to see these results and compare them with those obtained with the other methods. The aim is to show, soon at the beginning of the book, the potentiality, versatility, and generality of the RFV approach. In this way, we hope to intrigue the readers and convince them it is worthwhile studying this new approach and going on reading this book.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
A different situation, for instance, would be that different measurements were made with different measurement tapes randomly chosen and that the mean of the measured values were taken. In this case, it could be stated that the considered systematic contribution affects the measurement procedure in a random way.
- 2.
These values have been chosen because they correspond to the ± σ and ± 2σ intervals of a normal pdf.
- 3.
As a particular case, when the two uniform PDFs have the same width, the obtained PDF is triangular.
References
JCGM 100:2008, Evaluation of Measurement Data – Guide to the Expression of Uncertainty in Measurement, (GUM 1995 with minor corrections). Joint Committee for Guides in Metrology (2008). Available: http://www.bipm.org/en/publications/guides/gum.html
JCGM 101:2008, Evaluation of measurement data – Supplement 1 to the Guide to the expression of uncertainty in measurement – Propagation of distributions using a Monte Carlo method. Joint Committee for Guides in Metrology (2008). Available: http://www.bipm.org/en/publications/guides/gum.html
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Salicone, S., Prioli, M. (2018). A First, Preliminary Example. In: Measuring Uncertainty within the Theory of Evidence. Springer Series in Measurement Science and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-74139-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-74139-0_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-74137-6
Online ISBN: 978-3-319-74139-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)