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- W969051346 abstract "Statistics is the discipline responsible for the interpretation of data as scientific evidence. There is a broad statistical literature dealing with the interpretation of data as statistical evidence, the foundations of statistical inference, and the various statistical paradigms for measuring statistical inference. This chapter offers a general framework that enables the comparison and the evaluation of statistical paradigms claiming to measure the strength of statistical evidence in data. The framework is simple and general, consisting of only three key components. Three essential quantities for assessing and interpreting the strength of statistical evidence in data are: the measure of the strength of evidence, the probability that a particular study design will generate misleading evidence, and the probability that observed evidence is misleading. The advantages of a well-defined evidential framework are illustrated by examining the Likelihood paradigm in the context of multiple examinations of data and multiple comparisons. The Likelihood principle sets forth the conditions under which two experiments yield equivalent statistical evidence for two hypotheses of interest." @default.
- W969051346 created "2016-06-24" @default.
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- W969051346 date "2011-01-01" @default.
- W969051346 modified "2023-10-02" @default.
- W969051346 title "Likelihood and its Evidential Framework" @default.
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- W969051346 doi "https://doi.org/10.1016/b978-0-444-51862-0.50014-9" @default.
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