On Some Principles of Statistical Inference |
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Authors: | Nancy Reid David R Cox |
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Institution: | 1. Department of Statistics, University of Toronto, Toronto, Canada;2. Nuffield College, Oxford, UK |
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Abstract: | Statistical theory aims to provide a foundation for studying the collection and interpretation of data, a foundation that does not depend on the particular details of the substantive field in which the data are being considered. This gives a systematic way to approach new problems, and a common language for summarising results; ideally, the foundations and common language ensure that statistical aspects of one study, or of several studies on closely related phenomena, can be broadly accessible. We discuss some principles of statistical inference, to outline how these are, or could be, used to inform the interpretation of results, and to provide a greater degree of coherence for the foundations of statistics. |
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Keywords: | Ancillary Bayesian conditional likelihood models p‐values sufficient |
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