Statistical Evidence: A Likelihood Paradigm: 71 (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) - Image 1

£146.03

Chapman and Hall/CRC Statistical Evidence: A Likelihood Paradigm: 71 (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Name: Statistical Evidence: A Likelihood Paradigm: 71 (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
Brand: Chapman and Hall/CRC
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Description

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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Statistical Evidence: A Likelihood Paradigm (Monographs on Statistics and Applied Probability, 71, Volume 71)

Product type: ABIS BOOK

Brand: Chapman and Hall/CRC

Product Specifications

Brand: Chapman and Hall/CRC
Format: hardcover
ASIN: 0412044110
Category: Books > Subjects > Science, Nature & Maths > Mathematics > Probability & Statistics
Domain: Amazon UK
Release Date: 01 June 1997
Listed Since: 09 February 2007

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Chapman and Hall/CRC Statistical Evidence: A Likelihood Paradigm: 71 (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

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