Cited by 9,860Scientific Measurement and Uncertainty EvaluationProbabilistic and Robust Engineering DesignOptimal Experimental Design Methods

Describing the uncertainties in experimental results

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Moffat, Robert J.·1988·Experimental Thermal and Fluid Science

Abstract

It is no longer acceptable, in most circles, to present experimental results without describing the uncertainties involved. Besides its obvious role in publishing, uncertainty analysis provides the experimenter a rational way of evaluating the significance of the scatter on repeated trials. This can be a powerful tool in locating the source of trouble in a misbehaving experiment. To the user of the data, a statement (by the experimenter) of the range within which the results of the present experiment might have fallen by chance alone is of great help in deciding whether the present data agree with past results or differ from them. These benefits can be realized only if both the experimenter and the reader understand what an uncertainty analysis is, what it can do (and cannot do), and how to interpret its results. This paper begins with a general description of the sources of errors in engineering measurements and the relationship between error and uncertainty. Then the path of an uncertainty analysis is traced from its first step, identifying the intended true value of a measurement, through the quantitative estimation of the individual errors, to the end objective—the interpretation and reporting of the results. The basic mathematics of both single-sample and multiple-sample analysis are presented, as well as a technique for numerically executing uncertainty analyses when computerized data interpretation is involved. The material presented in this paper covers the method of…

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Authors
Moffat, R. J.
Affiliations
Stanford University (US)
Corresponding author
Moffat, Robert J.
Venue
Experimental Thermal and Fluid Science
Publisher
Elsevier BV
Published
1988-01
Volume
1
Issue
1
Pages
3-17
ISSN
0894-1777 (ISSN-L)
OpenAlex
W2056754315
Cited by
9,860
References
0
Citations by year
2026: 880 · 2025: 1053 · 2024: 911 · 2023: 775 · 2022: 766 · 2021: 720 · 2020: 674 · 2019: 565 · 2018: 457 · 2017: 372 · 2016: 315 · 2015: 230 · 2014: 229 · 2013: 202 · 2012: 214
FWCI
18.93
Type
journal article
Language
en
Open access
Locations
Experimental Thermal and Fluid Science (publishedVersion, cc-by-nc-nd)
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Scientific Measurement and Uncertainty Evaluation
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Probabilistic and Robust Engineering Design
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
Keywords
uncertainty analysis, measurement error, engineering measurement, error propagation, measurement uncertainty, single-sample analysis, multiple sample analysis, repeatability of measurements

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