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  1. (1 other version)Interpretations of probability.Alan Hájek - 2007 - Stanford Encyclopedia of Philosophy.
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  • Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science.Bernd I. Dahn - 1978 - Studia Logica 37 (2):213-219.
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  • Duhem's problem, the bayesian way, and error statistics, or "what's belief got to do with it?".Deborah G. Mayo - 1997 - Philosophy of Science 64 (2):222-244.
    I argue that the Bayesian Way of reconstructing Duhem's problem fails to advance a solution to the problem of which of a group of hypotheses ought to be rejected or "blamed" when experiment disagrees with prediction. But scientists do regularly tackle and often enough solve Duhemian problems. When they do, they employ a logic and methodology which may be called error statistics. I discuss the key properties of this approach which enable it to split off the task of testing auxiliary (...)
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  • The Foundations of Scientific Inference.Wesley C. Salmon - 1967 - [Pittsburgh]: University of Pittsburgh Pre.
    Not since Ernest Nagel’s 1939 monograph on the theory of probability has there been a comprehensive elementary survey of the philosophical problems of probablity and induction. This is an authoritative and up-to-date treatment of the subject, and yet it is relatively brief and nontechnical. Hume’s skeptical arguments regarding the justification of induction are taken as a point of departure, and a variety of traditional and contemporary ways of dealing with this problem are considered. The author then sets forth his own (...)
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  • (3 other versions)Theory and Evidence.Clark Glymour - 1982 - Erkenntnis 18 (1):105-130.
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  • Logic of Statistical Inference.Ian Hacking - 1965 - Cambridge, England: Cambridge University Press.
    One of Ian Hacking's earliest publications, this book showcases his early ideas on the central concepts and questions surrounding statistical reasoning. He explores the basic principles of statistical reasoning and tests them, both at a philosophical level and in terms of their practical consequences for statisticians. Presented in a fresh twenty-first-century series livery, and including a specially commissioned preface written by Jan-Willem Romeijn, illuminating its enduring importance and relevance to philosophical enquiry, Hacking's influential and original work has been revived for (...)
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  • Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science.Deborah G. Mayo & Aris Spanos (eds.) - 2009 - New York: Cambridge University Press.
    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 (...)
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  • (1 other version)On the Concept of a Random Sequence.Alonzo Church - 1940 - Bulletin of the American Mathematical Society 46 (2):130--135.
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  • Computability and Randomness.André Nies - 2008 - Oxford, England: Oxford University Press UK.
    The interplay between computability and randomness has been an active area of research in recent years, reflected by ample funding in the USA, numerous workshops, and publications on the subject. The complexity and the randomness aspect of a set of natural numbers are closely related. Traditionally, computability theory is concerned with the complexity aspect. However, computability theoretic tools can also be used to introduce mathematical counterparts for the intuitive notion of randomness of a set. Recent research shows that, conversely, concepts (...)
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  • Understanding Scientific Reasoning.Ronald N. Giere, John Bickle & Robert F. Mauldin - 2006 - Fort Worth, TX, USA: Cengage Learning.
    Understanding Scientific Reasoning, Fifth Edition, develops critical reasoning skills and guides students in the improvement of their scientific and technological literacy. The authors teach students how to understand and critically evaluate the scientific information they encounter in both textbooks and the popular media. With its focus on scientific pedagogy, Understanding Scientific Reasoning helps students learn how to examine scientific reports with a reasonable degree of sophistication. The book also explains how to reason through case studies using the same informal logic (...)
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  • The discovery of argon: A case for learning from data?Aris Spanos - 2010 - Philosophy of Science 77 (3):359-380.
    Rayleigh and Ramsay discovered the inert gas argon in the atmospheric air in 1895 using a carefully designed sequence of experiments guided by an informal statistical analysis of the resulting data. The primary objective of this article is to revisit this remarkable historical episode in order to make a case that the error‐statistical perspective can be used to bring out and systematize (not to reconstruct) these scientists' resourceful ways and strategies for detecting and eliminating error, as well as dealing with (...)
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  • The rise of scientific philosophy.Hans Reichenbach - 1951 - Berkeley,: University of California Press.
    The student of philosophy usually is not irritated by obscure formulations. On the contrary, reading the quoted passage he would presumably be convinced ...
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  • (1 other version)Scientific Explanation and the Causal Structure of the World.Wesley C. Salmon - 1984 - Princeton University Press.
    The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...)
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  • Choice and chance: an introduction to inductive logic.Brian Skyrms - 1975 - Encino, Calif.: Dickenson Pub. Co..
    Preface. I. BASICS OF LOGIC. Introduction. The Structure of Simple Statements. The Structure of Complex Statements. Simple and Complex Properties. Validity. 2. PROBABILITY AND INDUCTIVE LOGIC. Introduction. Arguments. Logic. Inductive versus Deductive Logic. Epistemic Probability. Probability and the Problems of Inductive Logic. 3. THE TRADITIONAL PROBLEM OF INDUCTION. Introduction. Hume’s Argument. The Inductive Justification of Induction. The Pragmatic Justification of Induction. Summary. IV. THE GOODMAN PARADOX AND THE NEW RIDDLE OF INDUCTION. Introduction. Regularities and Projection. The Goodman Paradox. The Goodman (...)
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  • Curve Fitting, the Reliability of Inductive Inference, and the Error‐Statistical Approach.Aris Spanos - 2007 - Philosophy of Science 74 (5):1046-1066.
    The main aim of this paper is to revisit the curve fitting problem using the reliability of inductive inference as a primary criterion for the ‘fittest' curve. Viewed from this perspective, it is argued that a crucial concern with the current framework for addressing the curve fitting problem is, on the one hand, the undue influence of the mathematical approximation perspective, and on the other, the insufficient attention paid to the statistical modeling aspects of the problem. Using goodness-of-fit as the (...)
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  • Severe testing as a basic concept in a neyman–pearson philosophy of induction.Deborah G. Mayo & Aris Spanos - 2006 - British Journal for the Philosophy of Science 57 (2):323-357.
    Despite the widespread use of key concepts of the Neyman–Pearson (N–P) statistical paradigm—type I and II errors, significance levels, power, confidence levels—they have been the subject of philosophical controversy and debate for over 60 years. Both current and long-standing problems of N–P tests stem from unclarity and confusion, even among N–P adherents, as to how a test's (pre-data) error probabilities are to be used for (post-data) inductive inference as opposed to inductive behavior. We argue that the relevance of error probabilities (...)
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  • Philosophical Theories of Probability.Donald Gillies - 2000 - New York: Routledge.
    The Twentieth Century has seen a dramatic rise in the use of probability and statistics in almost all fields of research. This has stimulated many new philosophical ideas on probability. _Philosophical Theories of Probability_ is the first book to present a clear, comprehensive and systematic account of these various theories and to explain how they relate to one another. Gillies also offers a distinctive version of the propensity theory of probability, and the intersubjective interpretation, which develops the subjective theory.
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  • (2 other versions)Error and the growth of experimental knowledge.Deborah Mayo - 1996 - International Studies in the Philosophy of Science 15 (1):455-459.
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  • Theory and Evidence.Clark N. Glymour - 1980 - Princeton University Press.
    The Description for this book, Theory and Evidence, will be forthcoming.
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  • (1 other version)The theory of probability.Hans Reichenbach - 1949 - Berkeley,: University of California Press.
    We must restrict to mere probability not only statements of comparatively great uncertainty, like predictions about the weather, where we would cautiously ...
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  • Choice and chance.Brian Skyrms - 1966 - Belmont, Calif.,: Dickenson Pub. Co..
    This definitive survey of the hottest issues in inductive logic sets the stage for further classroom discussion.
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  • Scientific reasoning: the Bayesian approach.Peter Urbach & Colin Howson - 1993 - Chicago: Open Court. Edited by Peter Urbach.
    Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...
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  • (1 other version)On the Mathematical Foundations of Theoretical Statistics.Ronald A. Fisher - 1922 - Philosophical Transactions of the Royal Society of London. Series A 222:309--368.
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  • The Literature on von Mises' Kollektivs Revisited.Per Martin-löf - 1969 - Theoria 35 (1):12-37.
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  • Frequentist probability and frequentist statistics.J. Neyman - 1977 - Synthese 36 (1):97 - 131.
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  • (1 other version)The Rise of Scientific Philosophy.HANS REICHENBACH - 1951 - Philosophy 27 (102):269-270.
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  • (1 other version)The Rise of Scientific Philosophy.Hans Reichenbach - 1951 - British Journal for the Philosophy of Science 2 (8):334-337.
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  • Methodology in Practice: Statistical Misspecification Testing.Deborah G. Mayo & Aris Spanos - 2004 - Philosophy of Science 71 (5):1007-1025.
    The growing availability of computer power and statistical software has greatly increased the ease with which practitioners apply statistical methods, but this has not been accompanied by attention to checking the assumptions on which these methods are based. At the same time, disagreements about inferences based on statistical research frequently revolve around whether the assumptions are actually met in the studies available, e.g., in psychology, ecology, biology, risk assessment. Philosophical scrutiny can help disentangle 'practical' problems of model validation, and conversely, (...)
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  • Theory testing in economics and the error-statistical perspective.Aris Spanos - 2009 - In Deborah G. Mayo & Aris Spanos (eds.), Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science. New York: Cambridge University Press. pp. 1-419.
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  • Is frequentist testing vulnerable to the base-rate fallacy?Aris Spanos - 2010 - Philosophy of Science 77 (4):565-583.
    This article calls into question the charge that frequentist testing is susceptible to the base-rate fallacy. It is argued that the apparent similarity between examples like the Harvard Medical School test and frequentist testing is highly misleading. A closer scrutiny reveals that such examples have none of the basic features of a proper frequentist test, such as legitimate data, hypotheses, test statistics, and sampling distributions. Indeed, the relevant error probabilities are replaced with the false positive/negative rates that constitute deductive calculations (...)
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  • (2 other versions)Error and the Growth of Experimental Knowledge.Deborah Mayo - 1997 - British Journal for the Philosophy of Science 48 (3):455-459.
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  • Probability, Statistics and Truth.Richard von Mises & Hilda Geiringer - 1959 - Philosophy of Science 26 (4):387-388.
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  • The Logical Foundations of Statistical Inference.Henry Ely Kyburg - 1974 - Dordrecht and Boston: Reidel.
    At least one of these conceptions of probability underlies any theory of statistical inference (or, to use Neyman's phrase, 'inductive behavior'). ...
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  • Probability, Statistics and Truth. [REVIEW]M. G. White - 1941 - Philosophical Review 50 (1):81-82.
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  • One problem about induction.Ian Hacking - 1968 - In Imre Lakatos (ed.), The problem of inductive logic. Amsterdam,: North Holland Pub. Co.. pp. 44--58.
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  • Philosophical Problems of Statistical Inference.Teddy Seidenfeld - 1981 - Philosophical Review 90 (2):295-298.
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  • Foundations of probability theory, statistical inference, and statistical theories of science.W. Hooker, C., Harper (ed.) - 1975 - Springer.
    In May of 1973 we organized an international research colloquium on foundations of probability, statistics, and statistical theories of science at the University of Western Ontario. During the past four decades there have been striking formal advances in our understanding of logic, semantics and algebraic structure in probabilistic and statistical theories. These advances, which include the development of the relations between semantics and metamathematics, between logics and algebras and the algebraic-geometrical foundations of statistical theories (especially in the sciences), have led (...)
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  • (1 other version)On the Concept of a Random Sequence.Alonzo Church - 1940 - Journal of Symbolic Logic 5 (2):71-72.
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