The Likelihood Paradigm for Statistical Evidence

Richard Royall

in The Nature of Scientific Evidence

Published by University of Chicago Press

Published in print October 2004 | ISBN: 9780226789552
Published online February 2013 | e-ISBN: 9780226789583 | DOI:
The Likelihood Paradigm for Statistical Evidence

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Statistical methods aim to answer a variety of questions about observations. A simple example occurs when a fairly reliable test for a condition or substance, C, has given a positive result. Three important types of questions are: Should this observation lead me to believe that C is present? Does this observation justify my acting as if C were present? Is this observation evidence that C is present? This chapter distinguishes among these three questions in terms of the variables and principles that determine their answers. It then uses this framework to understand the scope and limitations of current methods for interpreting statistical data as evidence. By “statistical evidence,” we mean observations that are interpreted under a probability model. Questions of the third type, concerning the evidential interpretation of statistical data, are central to many applications of statistics in science. The chapter shows that for answering them, current statistical methods are seriously flawed. It looks for the source of the problems and proposes a solution based on the law of likelihood.

Keywords: statistical methods; statistical evidence; observations; statistics; statistical data; science; law of likelihood

Chapter.  13915 words.  Illustrated.

Subjects: Animal Pathology and Diseases

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