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 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 modeling 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.
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By means of a series of exchanges between the editors and leaders from 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 modeling practice.About the Author:
Deborah G. Mayo is a professor in the Department of Philosophy at Virginia Polytechnic Institute and State University, known as Virginia Tech, and holds a visiting appointment in the Center for the Philosophy of Natural and Social Science at the London School of Economics. She is the author of Error and the Growth of Experimental Knowledge, which in 1998 won the Lakatos Prize, awarded for the most outstanding contribution to philosophy of science during the previous six years. Professor Mayo coedited the volume Acceptable Evidence: Science and Values in Risk Management (1991, with R. Hollander) and has published numerous articles on the philosophy and history of science and foundations of statistics and experimental inference and in interdisciplinary works on evidence relevant for regulation and policy.
Aris Spanos is Wilson Schmidt Professor of Economics at Virginia Tech. He has also taught at Birkbeck College, London, the University of Cambridge, the University of California and the University of Cyprus. Professor Spanos is the author of Probability Theory and Statistical Inference (1999) and Statistical Foundations of Econometric Modeling (1986), both published by Cambridge University Press. Professor Spanos's research has appeared in journals such as the Journal of Econometrics, Econometric Theory, Econometric Reviews, and Philosophy of Science. His research interests include the philosophy and methodology of statistical inference and modeling, foundational problems in statistics, statistical adequacy, misspecification testing and respecification, resampling and simulation techniques and modeling speculative prices.
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