Statistical Evidence: A Likelihood Paradigm

Richard Royall

© 1997 - Chapman and Hall/CRC
Published June 1, 1997
Reference - 191 Pages
ISBN 9780412044113 - CAT# C4411
Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability

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  • Introduces a completely new paradigm and explains how to use it
  • Provides theory and methods for both measurement and graphical representation of statistical evidence
  • Helps resolve the frequentist versus Bayesian dilemma
  • Summary

    Interpreting statistical data as evidence, Statistical Evidence: A Likelihood Paradigm focuses on the law of likelihood, fundamental to solving many of the problems associated with interpreting data in this way. Statistics has long neglected this principle, resulting in a seriously defective methodology. This book redresses the balance, explaining why science has clung to a defective methodology despite its well-known defects. After examining the strengths and weaknesses of the work of Neyman and Pearson and the Fisher paradigm, the author proposes an alternative paradigm which provides, in the law of likelihood, the explicit concept of evidence missing from the other paradigms. At the same time, this new paradigm retains the elements of objective measurement and control of the frequency of misleading results, features which made the old paradigms so important to science. The likelihood paradigm leads to statistical methods that have a compelling rationale and an elegant simplicity, no longer forcing the reader to choose between frequentist and Bayesian statistics.


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