03664nam 22006732 450 991079206860332120151005020623.01-107-23583-91-139-61618-81-139-62548-91-139-61060-01-139-60893-21-139-13508-21-139-61246-81-299-25771-2(CKB)2560000000098642(EBL)1099890(OCoLC)827947115(SSID)ssj0000833623(PQKBManifestationID)11449185(PQKBTitleCode)TC0000833623(PQKBWorkID)10936473(PQKB)10304236(UkCbUP)CR9781139135085(MiAaPQ)EBC1099890(Au-PeEL)EBL1099890(CaPaEBR)ebr10659313(CaONFJC)MIL457021(PPN)261312898(EXLCZ)99256000000009864220110729d2013|||| uy| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierMeasurement uncertainty and probability /Robin Willink[electronic resource]Cambridge :Cambridge University Press,2013.1 online resource (xvii, 276 pages) digital, PDF file(s)Title from publisher's bibliographic system (viewed on 05 Oct 2015).1-107-02193-6 1-139-62176-9 Includes bibliographical references and index.Foundational 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?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.Measurement Uncertainty & ProbabilityMeasurement uncertainty (Statistics)ProbabilitiesMeasurement uncertainty (Statistics)Probabilities.519.2SCI055000bisacshWillink Robin1961-1558996UkCbUPUkCbUPBOOK9910792068603321Measurement uncertainty and probability3823870UNINA