Hidden Bibliographic Details
ISBN: | 9789812775511 981277551X 9789812383563 9812383565 981277551X 1281928216 9781281928214 9786611928216 6611928219
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Notes: | Includes bibliographical references (pages 313-323) and index. English.
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Summary: | A multi-level introduction to Bayesian reasoning (as opposed to "conventional statistics") and its applications to data analysis. The basic ideas of this approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference; combination of results; treatment of uncertainty due to systematic errors and background; comparison of hypotheses; unfolding of experimental distributions; upper/lower bounds in frontier-type measurements. Approximate methods for routine use are derived and are shown often to coincide - under well-defined assumptions - with "standard" methods, which can therefore be seen as special cases of the more general Bayesian methods. In dealing with uncertainty in measurements, modern metrological ideas are utilized, including the ISO classification of uncertainty into type A and type B. These are shown to fit well into the Bayesian framework.
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Other form: | Print version: D'Agostini, Giulio. Bayesian Reasoning in Data Analysis : A Critical Introduction. Singapore : World Scientific Publishing Company, ©2003 9789812383563
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