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＜電子ブック＞
Introduction to Statistics in Metrology / by Stephen Crowder, Collin Delker, Eric Forrest, Nevin Martin

版	1st ed. 2020.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2020
大きさ	XXI, 347 p. 111 illus., 101 illus. in color : online resource
著者標目	*Crowder, Stephen author Delker, Collin author Forrest, Eric author Martin, Nevin author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Measurement LCSH:Measuring instruments LCSH:Electrical engineering LCSH:Mechanical engineering FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences FREE:Measurement Science and Instrumentation FREE:Statistical Theory and Methods FREE:Electrical and Electronic Engineering FREE:Mechanical Engineering
一般注記	1. Introduction -- 2. Basic Concepts -- 3. The International System of Units (SI), Traceability, and Calibration -- 4. Introduction to Statistics and Probability -- 5. Measurement Uncertainty in Decision Making -- 6. The Measurement Model and Uncertainty -- 7. Analytical Methods for the Propagation of Uncertainties -- 8. Monte Carlo Methods for the Propagation of Uncertainties -- 9. Determining Uncertainties in Fitted Curves -- 10. Design of Experiments in Metrology -- 11. Special Topics in Metrology -- 12. Summary and Acknowledgments This book provides an overview of the application of statistical methods to problems in metrology, with emphasis on modelling measurement processes and quantifying their associated uncertainties. It covers everything from fundamentals to more advanced special topics, each illustrated with case studies from the authors' work in the Nuclear Security Enterprise (NSE). The material provides readers with a solid understanding of how to apply the techniques to metrology studies in a wide variety of contexts. The volume offers particular attention to uncertainty in decision making, design of experiments (DOEx) and curve fitting, along with special topics such as statistical process control (SPC), assessment of binary measurement systems, and new results on sample size selection in metrology studies. The methodologies presented are supported with R script when appropriate, and the code has been made available for readers to use in their own applications. Designed to promote collaboration between statistics and metrology, this book will be of use to practitioners of metrology as well as students and researchers in statistics and engineering disciplines HTTP:URL=https://doi.org/10.1007/978-3-030-53329-8

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