Measurement uncertainty and probability / Robin Willink.
"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 measuremen...
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| Year of Publication: | 2013 |
| Language: | English |
| Online Access: | |
| Physical Description: | xvii, 276 p. :; ill. |
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| 050 | 4 | |a QA276.8 |b .W56 2013 | |
| 082 | 0 | 4 | |a 519.2 |2 23 |
| 100 | 1 | |a Willink, Robin, |d 1961- | |
| 245 | 1 | 0 | |a Measurement uncertainty and probability |h [electronic resource] / |c Robin Willink. |
| 260 | |a Cambridge : |b Cambridge University Press, |c 2013. | ||
| 300 | |a xvii, 276 p. : |b ill. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 8 | |a 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. | |
| 520 | |a "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"-- |c Provided by publisher. | ||
| 533 | |a Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. | ||
| 650 | 0 | |a Measurement uncertainty (Statistics) | |
| 650 | 0 | |a Probabilities. | |
| 655 | 4 | |a Electronic books. | |
| 710 | 2 | |a ProQuest (Firm) | |
| 856 | 4 | 0 | |u https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=1099890 |z Click to View |