
ISO 13587:2012
ISO 13587:2012 Three statistical approaches for the assessment and interpretation of measurement uncertainty
CDN $312.00
Description
ISO/TR 13587:2012 is concerned with three basic statistical approaches for the evaluation and interpretation of measurement uncertainty: the frequentist approach including bootstrap uncertainty intervals, the Bayesian approach, and fiducial inference. The common feature of these approaches is a clearly delineated probabilistic interpretation or justification for the resulting uncertainty intervals. For each approach, the basic method is described and the fundamental underlying assumptions and the probabilistic interpretation of the resulting uncertainty are discussed. Each of the approaches is illustrated using two examples including an example from the ISO/IEC Guide 98-3 (Uncertainty of measurement ? Part 3: Guide to the expression of uncertainty in measurement (GUM:1995)). This document also includes a discussion of the relationship between the methods proposed in GUM Supplement 1 and these three statistical approaches.
Edition
1
Published Date
2012-07-13
Status
PUBLISHED
Pages
43
Format 
Secure PDF
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Abstract
ISO/TR 13587:2012 is concerned with three basic statistical approaches for the evaluation and interpretation of measurement uncertainty: the frequentist approach including bootstrap uncertainty intervals, the Bayesian approach, and fiducial inference. The common feature of these approaches is a clearly delineated probabilistic interpretation or justification for the resulting uncertainty intervals. For each approach, the basic method is described and the fundamental underlying assumptions and the probabilistic interpretation of the resulting uncertainty are discussed. Each of the approaches is illustrated using two examples including an example from the ISO/IEC Guide 98-3 (Uncertainty of measurement ? Part 3: Guide to the expression of uncertainty in measurement (GUM:1995)). This document also includes a discussion of the relationship between the methods proposed in GUM Supplement 1 and these three statistical approaches.
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