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  1. Hume's problem: induction and the justification of belief.Colin Howson - 2000 - New York: Oxford University Press.
    In the mid-eighteenth century David Hume argued that successful prediction tells us nothing about the truth of the predicting theory. But physical theory routinely predicts the values of observable magnitudes within very small ranges of error. The chance of this sort of predictive success without a true theory suggests that Hume's argument is flawed. However, Colin Howson argues that there is no flaw and examines the implications of this disturbing conclusion; he also offers a solution to one of the central (...)
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  • On bayesian measures of evidential support: Theoretical and empirical issues.Vincenzo Crupi, Katya Tentori & and Michel Gonzalez - 2007 - Philosophy of Science 74 (2):229-252.
    Epistemologists and philosophers of science have often attempted to express formally the impact of a piece of evidence on the credibility of a hypothesis. In this paper we will focus on the Bayesian approach to evidential support. We will propose a new formal treatment of the notion of degree of confirmation and we will argue that it overcomes some limitations of the currently available approaches on two grounds: (i) a theoretical analysis of the confirmation relation seen as an extension of (...)
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  • Irrelevant conjunction: Statement and solution of a new paradox.Vincenzo Crupi & Katya Tentori - 2010 - Philosophy of Science 77 (1):1-13.
    The so‐called problem of irrelevant conjunction has been seen as a serious challenge for theories of confirmation. It involves the consequences of conjoining irrelevant statements to a hypothesis that is confirmed by some piece of evidence. Following Hawthorne and Fitelson, we reconstruct the problem with reference to Bayesian confirmation theory. Then we extend it to the case of conjoining irrelevant statements to a hypothesis that is dis confirmed by some piece of evidence. As a consequence, we obtain and formally present (...)
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  • A Second Look at the Logic of Explanatory Power (with Two Novel Representation Theorems).Vincenzo Crupi & Katya Tentori - 2012 - Philosophy of Science 79 (3):365-385.
    We discuss the probabilistic analysis of explanatory power and prove a representation theorem for posterior ratio measures recently advocated by Schupbach and Sprenger. We then prove a representation theorem for an alternative class of measures that rely on the notion of relative probability distance. We end up endorsing the latter, as relative distance measures share the properties of posterior ratio measures that are genuinely appealing, while overcoming a feature that we consider undesirable. They also yield a telling result concerning formal (...)
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  • Probability, Frequency, and Reasonable Expectation.Richard Threlkeld Cox - 1946 - American Journal of Physics 14 (2):1-13.
    Probability, Frequency and Reasonable Expectation.
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  • Probability, Frequency and Reasonable Expectation.Richard T. Cox - 1946 - Journal of Symbolic Logic 37 (2):398-399.
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  • Logical Foundations of Evidential Support.Branden Fitelson - 2006 - Philosophy of Science 73 (5):500-512.
    Carnap's inductive logic (or confirmation) project is revisited from an "increase in firmness" (or probabilistic relevance) point of view. It is argued that Carnap's main desiderata can be satisfied in this setting, without the need for a theory of "logical probability." The emphasis here will be on explaining how Carnap's epistemological desiderata for inductive logic will need to be modified in this new setting. The key move is to abandon Carnap's goal of bridging confirmation and credence, in favor of bridging (...)
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  • A Probabilistic Theory of Causality.Alex C. Michalos - 1972 - Philosophy of Science 39 (4):560-561.
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  • Bayesian Confirmation Theory and The Likelihood Principle.Daniel Steel - 2007 - Synthese 156 (1):53-77.
    The likelihood principle (LP) is a core issue in disagreements between Bayesian and frequentist statistical theories. Yet statements of the LP are often ambiguous, while arguments for why a Bayesian must accept it rely upon unexamined implicit premises. I distinguish two propositions associated with the LP, which I label LP1 and LP2. I maintain that there is a compelling Bayesian argument for LP1, based upon strict conditionalization, standard Bayesian decision theory, and a proposition I call the practical relevance principle. In (...)
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  • A bayesian way to make stopping rules matter.Daniel Steel - 2003 - Erkenntnis 58 (2):213--227.
    Disputes between advocates of Bayesians and more orthodox approaches to statistical inference presuppose that Bayesians must regard must regard stopping rules, which play an important role in orthodox statistical methods, as evidentially irrelevant.In this essay, I show that this is not the case and that the stopping rule is evidentially relevant given some Bayesian confirmation measures that have been seriously proposed. However, I show that accepting a confirmation measure of this sort comes at the cost of rejecting two useful ancillaryBayesian (...)
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  • Is coherence truth conducive?Tomoji Shogenji - 1999 - Analysis 59 (4):338–345.
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  • Is coherence truth conducive?T. Shogenji - 1999 - Analysis 59 (4):338-345.
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  • The Logic of Explanatory Power.Jonah N. Schupbach & Jan Sprenger - 2011 - Philosophy of Science 78 (1):105-127.
    This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems, all of which show that this measure neatly corresponds to our explanatory intuitions. Finally, (...)
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  • Degree of Confirmation.Karl R. Popper - 1955 - Journal of Symbolic Logic 20 (3):304-305.
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  • Degree of confirmation.Karl R. Popper - 1954 - British Journal for the Philosophy of Science 5 (18):143-149.
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  • The Diversity Principle and the Little Scientist Hypothesis.Daniel Osherson & Riccardo Viale - 2000 - Foundations of Science 5 (2):239-253.
    The remarkable transition from helpless infant to sophisticatedfive-year-old has long captured the attention of scholars interested inthe discovery of knowledge. To explain these achievements, developmentalpsychologists often compare children's discovery procedures to those ofprofessional scientists. For the child to be qualified as a ``littlescientist'', however, intellectual development must be shown to derivefrom rational hypothesis selection in the face of evidence. In thepresent paper we focus on one dimension of rational theory-choice,namely, the relation between hypothesis confirmation and evidencediversity. Psychological research suggests cultural (...)
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  • New Hope for Shogenji's Coherence Measure.Jonah N. Schupbach - 2011 - British Journal for the Philosophy of Science 62 (1):125-142.
    I show that the two most devastating objections to Shogenji's formal account of coherence necessarily involve information sets of cardinality . Given this, I surmise that the problem with Shogenji's measure has more to do with his means of generalizing the measure than with the measure itself. I defend this claim by offering an alternative generalization of Shogenji's measure. This alternative retains the intuitive merits of the original measure while avoiding both of the relevant problems that befall it. In the (...)
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  • Log[p(h/eb)/p(h/b)] is the one true measure of confirmation.Peter Milne - 1996 - Philosophy of Science 63 (1):21-26.
    Plausibly, when we adopt a probabilistic standpoint any measure Cb of the degree to which evidence e confirms hypothesis h relative to background knowledge b should meet these five desiderata: Cb > 0 when P > P < 0 when P < P; Cb = 0 when P = P. Cb is some function of the values P and P assume on the at most sixteen truth-functional combinations of e and h. If P < P and P = P then (...)
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  • Confirmation, heuristics, and explanatory reasoning.Timothy McGrew - 2003 - British Journal for the Philosophy of Science 54 (4):553-567.
    Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods or (...)
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  • Evidential diversity and premise probability in young children's inductive judgment.Yafen Lo, Ashley Sides, Joseph Rozelle & Daniel Osherson - 2002 - Cognitive Science 26 (2):181-206.
    A familiar adage in the philosophy of science is that general hypotheses are better supported by varied evidence than by uniform evidence. Several studies suggest that young children do not respect this principle, and thus suffer from a defect in their inductive methodology. We argue that the diversity principle does not have the normative status that psychologists attribute to it, and should be replaced by a simple rule of probability. We then report experiments designed to detect conformity to the latter (...)
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  • Degree of Factual Support.John G. Kemeny & Paul Oppenheim - 1955 - Journal of Symbolic Logic 20 (2):190-190.
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  • Degree of factual support.John G. Kemeny & Paul Oppenheim - 1952 - Philosophy of Science 19 (4):307-324.
    We wish to give a precise formulation of the intuitive concept: The degree to which the known facts support a given hypothesis.
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  • Milne’s Argument for the Log‐Ratio Measure.Franz Huber - 2008 - Philosophy of Science 75 (4):413-420.
    This article shows that a slight variation of the argument in Milne 1996 yields the log‐likelihood ratio l rather than the log‐ratio measure r as “the one true measure of confirmation. ” *Received December 2006; revised December 2007. †To contact the author, please write to: Formal Epistemology Research Group, Zukunftskolleg and Department of Philosophy, University of Konstanz, P.O. Box X906, 78457 Konstanz, Germany; e‐mail: franz.huber@uni‐konstanz.de.
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  • Probability and Evidence.Paul Horwich - 1973 - Philosophical Review 82 (4):547.
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  • Corroboration, explanation, evolving probability, simplicity and a sharpened razor.I. J. Good - 1968 - British Journal for the Philosophy of Science 19 (2):123-143.
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  • Likelihoodism, Bayesianism, and relational confirmation.Branden Fitelson - 2007 - Synthese 156 (3):473-489.
    Likelihoodists and Bayesians seem to have a fundamental disagreement about the proper probabilistic explication of relational (or contrastive) conceptions of evidential support (or confirmation). In this paper, I will survey some recent arguments and results in this area, with an eye toward pinpointing the nexus of the dispute. This will lead, first, to an important shift in the way the debate has been couched, and, second, to an alternative explication of relational support, which is in some sense a "middle way" (...)
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  • A bayesian account of independent evidence with applications.Branden Fitelson - 2001 - Proceedings of the Philosophy of Science Association 2001 (3):S123-.
    outlined. This account is partly inspired by the work of C.S. Peirce. When we want to consider how degree of confirmation varies with changing I show that a large class of quantitative Bayesian measures of con-.
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  • A Bayesian Account of Independent Evidence with Applications.Branden Fitelson - 2001 - Philosophy of Science 68 (S3):S123-S140.
    A Bayesian account of independent evidential support is outlined. This account is partly inspired by the work of C. S. Peirce. I show that a large class of quantitative Bayesian measures of confirmation satisfy some basic desiderata suggested by Peirce for adequate accounts of independent evidence. I argue that, by considering further natural constraints on a probabilistic account of independent evidence, all but a very small class of Bayesian measures of confirmation can be ruled out. In closing, another application of (...)
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  • Measuring confirmation and evidence.Ellery Eells & Branden Fitelson - 2000 - Journal of Philosophy 97 (12):663-672.
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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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  • Evidence and Evolution: The Logic Behind the Science.Elliott Sober - 2008 - Cambridge University Press.
    How should the concept of evidence be understood? And how does the concept of evidence apply to the controversy about creationism as well as to work in evolutionary biology about natural selection and common ancestry? In this rich and wide-ranging book, Elliott Sober investigates general questions about probability and evidence and shows how the answers he develops to those questions apply to the specifics of evolutionary biology. Drawing on a set of fascinating examples, he analyzes whether claims about intelligent design (...)
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  • Methodologies of Pattern Recognition: [the Proceedings of the International Conference on Methodologies of Pattern Recognition Held at Honolulu, Hawaii, January 24-26, 1968].Satosi Watanabe - 1969 - New York, NY, USA: Wiley.
    "An attempt at a quantitative study of the formal aspects of the process of knowing, inferring, information, and learning" -- Preface.
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  • The logic of induction.Halina Mortimer - 1988 - New York: Halsted Press. Edited by I. Craig & A. G. Cohn.
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  • Probability and Evidence.Paul Horwich - 1982 - Cambridge: Cambridge University Press.
    In this influential study of central issues in the philosophy of science, Paul Horwich elaborates on an important conception of probability, diagnosing the failure of previous attempts to resolve these issues as stemming from a too-rigid conception of belief. Adopting a Bayesian strategy, he argues for a probabilistic approach, yielding a more complete understanding of the characteristics of scientific reasoning and methodology. Presented in a fresh twenty-first-century series livery, and including a specially commissioned preface written by Colin Howson, illuminating its (...)
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  • Measuring Confirmation and Evidence.Ellery Elles & Branden Fitelson - 2000 - Journal of Philosophy 97 (12):663-672.
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  • Probabilistic measures of causal strength.Branden Fitelson & Christopher Hitchcock - 2011 - In Phyllis McKay Illari Federica Russo (ed.), Causality in the Sciences. Oxford University Press. pp. 600--627.
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  • Probability and Evidence.Paul Horwich - 1984 - British Journal for the Philosophy of Science 35 (2):161-166.
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  • Bayesian confirmation.Roberto Festa - 1999 - In M. C. Galavotti & A. Pagnini (eds.), Experience, Reality, and Scientific Explanation. Kluwer Academic Publishers. pp. 55–87.
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  • Postscripts to `causation'.David Lewis - 1986 - In Philosophical Papers Vol. Ii. Oxford University Press.
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  • Confirmation.Alan Hájek & James M. Joyce - 2008 - In S. Psillos & M. Curd (eds.), The Routledge Companion to the Philosophy of Science. Routledge.
    Confirmation theory is intended to codify the evidential bearing of observations on hypotheses, characterizing relations of inductive “support” and “counter­support” in full generality. The central task is to understand what it means to say that datum E confirms or supports a hypothesis H when E does not logically entail H.
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  • Probability and the Weighing of Evidence.I. J. Good - 1950 - Philosophy 26 (97):163-164.
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  • Conjectures and Refutations.K. Popper - 1963 - Les Etudes Philosophiques 21 (3):431-434.
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  • A Treatise on Probability.J. M. Keynes - 1989 - British Journal for the Philosophy of Science 40 (2):219-222.
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