Statistical Evidence: A Likelihood Paradigm

Cox, D.R. (Series edited by)/ Reid, N. (Series edited by)/ Isham, Valerie (Series edited by)/ Tibshirani, R.J. (Series edited by)/ Louis, Thomas A. (Series edited by)/ Tong, Howell (Series edited by)/ Keiding, Niels (Series edited by)/ Royall, Richard (Author)

ISBN 10: 0412044110 / ISBN 13: 9780412044113

Published by Chapman & Hall, 1997

About this Item

191 pages. 9.00x5.75x0.75 inches. In Stock.

Seller Inventory # x-0412044110

Bibliographic Details

• Title: Statistical Evidence: A Likelihood Paradigm
• Publisher: Chapman & Hall
• Publication Date: 1997
• Language: English
• ISBN 10: 0412044110
• ISBN 13: 9780412044113
• Binding: Hardcover
• Condition: Brand New
• Weight: 0.44 kilograms

About this title

Synopsis

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.

About the Author

Richard Royall