MARC Record from Library of Congress

LEADER: 03189cam a2200361 i 4500
001 2012025873
003 DLC
005 20130613075929.0
008 120626s2013 enka b 001 0 eng
010 $a 2012025873
020 $a9781107021938 (hardback)
040 $aDLC$beng$cDLC$erda$dDLC
042 $apcc
050 00 $aQA276.8$b.W56 2013
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,$c2013.
300 $axvii, 276 pages :$billustrations ;$c26 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 (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.
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
856 42 $3Contributor biographical information$uhttp://www.loc.gov/catdir/enhancements/fy1211/2012025873-b.html
856 42 $3Publisher description$uhttp://www.loc.gov/catdir/enhancements/fy1211/2012025873-d.html
856 41 $3Table of contents only$uhttp://www.loc.gov/catdir/enhancements/fy1211/2012025873-t.html