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Introduction to statistics in metrology

Crowder, Stephen.

Introduction to statistics in metrology

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to statistics in metrologyby Stephen Crowder ... [et al.].
其他作者:	Crowder, Stephen.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	xxi, 347 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	MetrologyStatistical methods.
電子資源:	https://doi.org/10.1007/978-3-030-53329-8
ISBN:	9783030533298$q(electronic bk.)

Introduction to statistics in metrology
Introduction to statistics in metrology[electronic resource] /by Stephen Crowder ... [et al.]. - Cham :Springer International Publishing :2020. - xxi, 347 p. :ill., digital ;24 cm.

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.

ISBN: 9783030533298$q(electronic bk.)

Standard No.: 10.1007/978-3-030-53329-8doiSubjects--Topical Terms:

881636
Metrology
--Statistical methods.

LC Class. No.: QA465

Dewey Class. No.: 530.8

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505 0 $a 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.
520 $a 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.
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