A statistical model to the expression of uncertainty and confidence in measurement

Author

Iuculano, G. ; Gualtieri, G. Pellegrini ; Zanobini, A.

Author_Institution

Dept. of Electron. Eng., Florence Univ., Italy

Volume

2

fYear

2000

fDate

2000

Firstpage

1030

Abstract

The explicit recognition of uncertainty is central to any measurement process. In this work a computer-intensive approach is adopted to the estimation of uncertainty at a given coverage probability, that is, at a given region of confidence in a measurement process. The method is adaptable to a large range of situations and is based on the use of Monte Carlo approximation and bootstrap resampling iteration. An experimental model is examined to understand the applicability of the numerical technique and to check the potentiality of the proposed method

Keywords

Monte Carlo methods; iterative methods; measurement theory; measurement uncertainty; probability; sampling methods; Monte Carlo approximation; bootstrap resampling iteration; confidence; confidence belt; experimental model; probability; statistical model; uncertainty; Approximation methods; Belts; Measurement standards; Measurement uncertainty; Monte Carlo methods; Performance evaluation; Probability distribution; State estimation; Symmetric matrices; Weight measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2000. IMTC 2000. Proceedings of the 17th IEEE

Conference_Location

Baltimore, MD

ISSN

1091-5281

Print_ISBN

0-7803-5890-2

Type

conf

DOI

10.1109/IMTC.2000.848897

Filename

848897