| 000 | 03206cam a2200373 i 4500 | ||
|---|---|---|---|
| 001 | 17361907 | ||
| 005 | 20191121144812.0 | ||
| 008 | 120626s2013 enka b 001 0 eng | ||
| 010 | _a 2012025873 | ||
| 020 | _a9781107021938 (hardback) | ||
| 040 |
_aDLC _beng _erda _dDLC |
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| 042 | _apcc | ||
| 050 | 0 | 0 |
_aQA276.8 _b.W56 2013 |
| 082 | 0 | 0 |
_a519.2 _223 |
| 084 |
_aSCI055000 _2bisacsh |
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| 100 | 1 |
_aWillink, Robin, _d1961- |
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| 245 | 1 | 0 |
_aMeasurement uncertainty and probability / _cRobin Willink. |
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2013. |
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| 300 |
_axvii, 276 pages : _billustrations ; _c26 cm |
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| 336 |
_atext _2rdacontent |
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| 337 |
_aunmediated _2rdamedia |
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| 338 |
_avolume _2rdacarrier |
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| 504 | _aIncludes bibliographical references (pages 268-272) and index. | ||
| 505 | 8 | _aMachine 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"-- _cProvided by publisher. |
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| 650 | 0 | _aMeasurement uncertainty (Statistics) | |
| 650 | 0 | _aProbabilities. | |
| 650 | 7 |
_aSCIENCE / Physics. _2bisacsh |
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| 856 | 4 | 2 |
_3Publisher description _uhttp://www.loc.gov/catdir/enhancements/fy1211/2012025873-d.html |
| 856 | 4 | 1 |
_3Table of contents only _uhttp://www.loc.gov/catdir/enhancements/fy1211/2012025873-t.html |
| 906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
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| 942 |
_2udc _cBK |
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| 999 |
_c27629 _d27629 |
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