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Error and Inference
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  • Cited by 4
  • Cited by
    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Gandenberger, Greg 2015. A New Proof of the Likelihood Principle. The British Journal for the Philosophy of Science, Vol. 66, Issue. 3, p. 475.

    Todt, Oliver and Luján, José Luis 2014. Values and Decisions. Science, Technology, & Human Values, Vol. 39, Issue. 5, p. 720.

    Douglas, Heather and Magnus, P.D. 2013. State of the Field: Why novel prediction matters. Studies in History and Philosophy of Science Part A, Vol. 44, Issue. 4, p. 580.

    2010. Books of Critical Interest. Critical Inquiry, Vol. 36, Issue. 4, p. 807.

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  • Edited by Deborah G. Mayo, Virginia Polytechnic Institute and State University , Aris Spanos, Virginia Polytechnic Institute and State University

Book description

Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific practitioners are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing.

Reviews

‘Mayo and Spanos’s collection has injected new ideas into the study of scientific inference. This book offers a welcome bridge between current philosophy of science and scientific practice, providing the reader with new insights on important topics such as statistical inference, reliability, theory testing, causal modeling, and the relation between theory and experiment. The book will have a wide and enthusiastic readership among philosophers and scientists.’

Cristina Bicchieri - University of Pennsylvania

‘Error and Inference straddles philosophy and practice; its lessons should be taken seriously in both. The editors suppose that venerable philosophical problems surrounding induction, scientific inference, and objectivity can be solved. The essays in the book give support to that perspective. They also show that pressing practical problems of scientific inference and testing gain marked benefit from careful attention to philosophers’ accounts of what makes for evidence, rationality, and objectivity.’

Nancy Cartwright - London School of Economics

‘The error-probabilistic approach developed by Deborah Mayo and Aris Spanos is the main alternative to Bayesianism in contemporary philosophy of science. In this superb volume Mayo and Spanos face their critics and show that error-probabilism is able to solve most theoretical puzzles of statistical testing. If some issue in the field of inductive inference is bothering you, you will probably find an answer in this book.’

Francesco Guala - University of Milan

‘Mayo, an empirically minded philosopher, and Spanos, a philosophically minded economist, have succeeded beautifully in orchestrating a lively debate over methodological issues related to statistics and empirical testing that - unlike too much of the philosophy of science - speaks to the genuine issues that the practitioners of empirical sciences face daily. Their important volume deserves a broad readership.’

Kevin Hoover - Duke University

‘Mayo and Spanos continue their campaign to bring confirmation theory face-to-face with the methods of scientists, and now extend it to the history of science and to general theories too. This book begins with a fine introduction to Mayo’s error-statistical approach that makes the book a useful teaching tool. But then it carries forward the discussion of this approach with challenging papers from Glymour, Laudan, Achinstein, Worrall, and others.’

Alexander Rosenberg - Duke University

‘This is a wonderful volume. It contains original and stimulating essays by leading figures from both philosophy and statistics on notions of evidence and testing; on how these interact with ideas about causation, explanation, and scientific rationality; and much more besides. The volume also features detailed and illuminating exchanges between the contributors. A must-read for anyone with an interest in these topics.’

Jim Woodward - California Institute of Technology

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