Measurement uncertainty and probability - Info and Reading Options
By Robin Willink
"Measurement uncertainty and probability" was published by Cambridge University Press in 2012 - enk, it has 276 pages and the language of the book is English.
“Measurement uncertainty and probability” Metadata:
- Title: ➤ Measurement uncertainty and probability
- Author: Robin Willink
- Language: English
- Number of Pages: 276
- Publisher: Cambridge University Press
- Publish Date: 2012
- Publish Location: enk
“Measurement uncertainty and probability” Subjects and Themes:
- Subjects: ➤ Probabilities - Measurement uncertainty (Statistics) - SCIENCE / Physics
Edition Specifications:
- Pagination: pages cm
Edition Identifiers:
- The Open Library ID: OL25404428M - OL16769154W
- Online Computer Library Center (OCLC) ID: 795763832 - 856939003
- Library of Congress Control Number (LCCN): 2012025873
- ISBN-13: 9781107021938
- All ISBNs: 9781107021938
AI-generated Review of “Measurement uncertainty and probability”:
"Measurement uncertainty and probability" Table Of Contents:
- 1- Machine generated contents note: Part I. Principles: 1. Introduction; 2. Foundational ideas in measurement; 3. Components of error or uncertainty; 4. Foundational ideas in probability and statistics; 5. The randomization of systematic errors; 6. Beyond the standard confidence interval; Part II. Evaluation of Uncertainty: 7. Final preparation; 8. Evaluation using the linear approximation; 9. Evaluation without the linear approximations; 10. Uncertainty information fit for purpose; Part III. Related Topics: 11. Measurement of vectors and functions; 12. Why take part in a measurement comparison?; 13. Other philosophies; 14. An assessment of objective Bayesian methods; 15. A guide to the expression of uncertainty in measurement; 16. Measurement near a limit - an insoluble problem?; References; Index.
"Measurement uncertainty and probability" Description:
The Open Library:
"A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science"--
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