MTU Cork Library Catalogue

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Statistical evidence : a likelihood paradigm / Richard M. Royall.

By: Royall, Richard M.
Material type: materialTypeLabelBookSeries: Monographs on statistics and applied probability (Series) ; 71.Publisher: Boca Raton, FL ; London : Chapman & Hall/CRC, 1997Description: xvi, 191 p. : ill. ; 23 cm. + hbk.ISBN: 0412044110.Subject(s): Estimation theory | Probabilities | Mathematical statisticsDDC classification: 519.5
Contents:
The first principle -- Neyman-Pearson theory -- Fisherian theory -- Paradigms for statistics -- Resolving the paradoxes from the old paradigms -- Looking at likelihoods -- Nuisance parameters -- Bayesian statistical inference.
Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
General Lending MTU Bishopstown Library Lending 519.5 (Browse shelf(Opens below)) 1 Available 00071384
Total holds: 0

Enhanced descriptions from Syndetics:

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.

Originally published: London ; New York : Chapman & Hall, 1997.

Includes bibliographical references (pages 181-187) and index.

The first principle -- Neyman-Pearson theory -- Fisherian theory -- Paradigms for statistics -- Resolving the paradoxes from the old paradigms -- Looking at likelihoods -- Nuisance parameters -- Bayesian statistical inference.

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