MARC Record from Library of Congress

LEADER: 02820nam a22003378i 4500
001 2012025873
003 DLC
005 20120803111105.0
008 120626s2012 enk b 001 0 eng
010 $a 2012025873
020 $a9781107021938
040 $aDLC$beng$cDLC$erda
042 $apcc
050 00 $aQA276.8$b.W56 2012
082 00 $a519.2$223
084 $aSCI055000$2bisacsh
100 1 $aWillink, Robin,$d1961-
245 10 $aMeasurement uncertainty and probability /$cRobin Willink.
264 1 $aCambridge :$bCambridge University Press,$c2012.
263 $a1211
300 $apages cm
336 $atext$2rdacontent
337 $aunmediated$2rdamedia
338 $avolume$2rdacarrier
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.
504 $aIncludes bibliographical references 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.
650 0 $aMeasurement uncertainty (Statistics)
650 0 $aProbabilities.
650 7 $aSCIENCE / Physics.$2bisacsh
856 42 $3Cover image$uhttp://assets.cambridge.org/97811070/21938/cover/9781107021938.jpg