An Introduction to Statistical Issues and Methods in Metrology for Physical Science and Engineering

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2014_Vardeman_IntroductionStatistical.PDF (1.94 MB)
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Date
2014-01-01
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Vardeman, Stephen
Hamada, Michael
Burr, Tom
Morris, Max
Wendelberger, Joanne
Jobe, J. Marcus
Moore, Leslie
Wu, Huaiquing
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Vardeman, Stephen
University Professor Emeritus
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Statistics
As leaders in statistical research, collaboration, and education, the Department of Statistics at Iowa State University offers students an education like no other. We are committed to our mission of developing and applying statistical methods, and proud of our award-winning students and faculty.
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Industrial and Manufacturing Systems Engineering
The Department of Industrial and Manufacturing Systems Engineering teaches the design, analysis, and improvement of the systems and processes in manufacturing, consulting, and service industries by application of the principles of engineering. The Department of General Engineering was formed in 1929. In 1956 its name changed to Department of Industrial Engineering. In 1989 its name changed to the Department of Industrial and Manufacturing Systems Engineering.
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StatisticsIndustrial and Manufacturing Systems Engineering
Abstract

This article provides an overview of the interplay between statistics and measurement. Measurement quality affects inference from data collected and analyzed using statistical methods while appropriate data analysis quantifies the quality of measurements. This article brings material on statistics and measurement together in one place as a resource for practitioners. Both frequentist and Bayesian methods are discussed.
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This article is published as Vardeman, Stephen, Michael S. Hamada, Tom Burr, Max Morris, Joanne Wendelberger, J. Marcus Jobe, Leslie Moore, and Huaiquing Wu. "An introduction to statistical issues and methods in metrology for physical science and engineering." Journal of Quality Technology 46, no. 1 (2014): 33-62. DOI: 10.1080/00224065.2014.11917953. Posted with permission.
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http://doi.org/10.1080/00224065.2014.11917953
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https://dr.lib.iastate.edu/handle/20.500.12876/90450
Subject Categories
Statistics and Probability
Keywords
Accuracy, Bayesian, Calibration, Control Chart, Frequentist, Gauge R&R, Linearity, Measurement Error, One- and Two-Sample Problems, Precision, Quantization Error, Random-Effects Model, Regression, Repeatability, Reproducibility, Stability, Type A and B Uncertainties, Validity
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Wed Jan 01 00:00:00 UTC 2014
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