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Author: Richard Royall
Publisher: Routledge
ISBN: 1351414550
Category : Mathematics
Languages : en
Pages : 212
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Book 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.
Author: Richard Royall
Publisher: Routledge
ISBN: 1351414550
Category : Mathematics
Languages : en
Pages : 212
Get Book Here
Book 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.
Author: Michael Evans
Publisher: CRC Press
ISBN: 148224280X
Category : Mathematics
Languages : en
Pages : 252
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Book Description
This book provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It attempts to establish a gold standard for how a statistical analysis should proceed. The book illustrates relative belief theory using many examples and describes the strengths and weaknesses of the theory. The author also addresses fundamental statistical issues, including the meaning of probability, the role of subjectivity, the meaning of objectivity, and the role of infinity and continuity.
Author: Bill Thompson
Publisher: Springer Science & Business Media
ISBN: 0387400540
Category : Mathematics
Languages : en
Pages : 155
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Book Description
The purpose of this book is to discuss whether statistical methods make sense. The present volume begins the task of providing interpretations and explanations of several theories of statistical evidence. It should be relevant to anyone interested in the logic of experimental science. Have we achieved a true Foundation of Statistics? We have made the link with one widely accepted view of science and we have explained the senses in which Bayesian statistics and p-values allow us to draw conclusions. This book has substantial implications for all users of Statistical methods.
Author: Colin Aitken
Publisher: John Wiley & Sons
ISBN: 047001122X
Category : Mathematics
Languages : en
Pages : 540
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Book Description
The first edition of Statistics and the Evaluation of Evidence for Forensic Scientists established itself as a highly regarded authority on this area. Fully revised and updated, the second edition provides significant new material on areas of current interest including: Glass Interpretation Fibres Interpretation Bayes’ Nets The title presents comprehensive coverage of the statistical evaluation of forensic evidence. It is written with the assumption of a modest mathematical background and is illustrated throughout with up-to-date examples from a forensic science background. The clarity of exposition makes this book ideal for all forensic scientists, lawyers and other professionals in related fields interested in the quantitative assessment and evaluation of evidence. 'There can be no doubt that the appreciation of some evidence in a court of law has been greatly enhanced by the sound use of statistical ideas and one can be confident that the next decade will see further developments, during which time this book will admirably serve those who have cause to use statistics in forensic science.' D.V. Lindley
Author: Stephen D. Simon
Publisher: Oxford University Press, USA
ISBN: 9780198567615
Category : Medical
Languages : en
Pages : 197
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Book Description
Aimed at students and researchers in statistics and in the medical and health care sector as well as those who use and assess medical data, this work addresses common pitfalls in experimental design, focusing on the errors and misleading data that stem from flawed experiments and analytical methods in medical research.
Author: David Aronson
Publisher: John Wiley & Sons
ISBN: 1118160584
Category : Business & Economics
Languages : en
Pages : 572
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Book Description
Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.
Author: MyoungJin Kim
Publisher: Jones & Bartlett Publishers
ISBN: 1284088375
Category : Medical
Languages : en
Pages : 428
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Book Description
Statistics for Evidence-Based Practice in Nursing, Second Edition presents statistics in a readable, user-friendly manner for both graduate students and the professional nurse.
Author: Mark L. Taper
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 600
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Book Description
Mark Taper, Subhash Lele and an esteemed group of contributors explore the relationships among hypotheses, models, data and interference on which scientific progress rests in an attempt to develop a new quantitative framework for evidence.
Author: Stephen D. Simon
Publisher: OUP Oxford
ISBN: 0191588229
Category : Medical
Languages : en
Pages : 216
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Book Description
Statistical Evidence in Medical Trials is a lucid, well-written and entertaining text that addresses common pitfalls in evaluating medical research. Including extensive use of publications from the medical literature and a non-technical account of how to appraise the quality of evidence presented in these publications, this book is ideal for health care professionals, students in medical or nursing schools, researchers and students in statistics, and anyone needing to assess the evidence published in medical journals. Stephen D. Simon earned a Ph.D. in statistics from the University of Iowa in 1982. He currently works as a research biostatistician at Children's Mercy Hospitals and Clinics in Kansas City, MO. He has authored or co-authored over 60 publications in a variety of medical and statistical journals, four of which have won awards. He has given a wide range of lectures and classes on statistics, evidence based medicine, research ethics, and quality control.
Author: Richard Royall
Publisher: Routledge
ISBN: 1351414569
Category : Mathematics
Languages : en
Pages : 191
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Book 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.
