MARC record from Internet Archive

LEADER: 02941cam 2200409 i 4500
001 9924570090001661
005 20171214130257.0
008 140115s2013 enka b 001 0 eng
010 $a2012025873
015 $aGBB288134$2bnb
016 7 $a016162588$2Uk
019 $a830816727$a839399554
020 $a9781107021938 (hardback)
020 $a1107021936 (hardback)
035 $a(OCoLC)795763832
035 $a(OCoLC)ocn795763832
040 $aDLC$beng$erda$cDLC$dBTCTA$dOCLCO$dBDX$dUKMGB$dCDX$dSTF$dCUD$dYDXCP$dNLE$dCAI$dBWX$dCUT$dOCLCF
042 $apcc
049 $aCNUM
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
504 $aIncludes bibliographical references (pages 268-272) and index.
505 0 $aFoundational ideas in measurement -- Components of error or uncertainty -- Foundational ideas in probability and statistics -- The randomization of systematic errors -- Beyond the standard confidence interval -- Final preparation -- Evaluation using the linear approximation -- Evaluation without the linear approximation -- Uncertainty information fit for purpose -- Measurement of vectors and functions -- Why take part in a measurement comparison? -- Other philosophies -- An assessment of objective Bayesian methods -- Guide to the expression of uncertainty in measurement -- Measurement near a limit, an insoluble problem?
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.
650 0 $aMeasurement uncertainty (Statistics)
650 0 $aProbabilities.
947 $fSCIENCE$hBOOK$p$85.14$q1
949 $aQA276.8 .W56 2013$i31786102873483
994 $a92$bCNU