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  1. Bayes' theorem.James Joyce - 2008 - Stanford Encyclopedia of Philosophy.
    Bayes' Theorem is a simple mathematical formula used for calculating conditional probabilities. It figures prominently in subjectivist or Bayesian approaches to epistemology, statistics, and inductive logic. Subjectivists, who maintain that rational belief is governed by the laws of probability, lean heavily on conditional probabilities in their theories of evidence and their models of empirical learning. Bayes' Theorem is central to these enterprises both because it simplifies the calculation of conditional probabilities and because it clarifies significant features of subjectivist position. Indeed, (...)
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  • When probabilistic support is inductive.Alberto Mura - 1990 - Philosophy of Science 57 (2):278-289.
    This note makes a contribution to the issue raised in a paper by Popper and Miller (1983) in which it was claimed that probabilistic support is purely deductive. Developing R. C. Jeffrey's remarks, a new general approach to the crucial concept of "going beyond" is here proposed. By means of it a quantitative measure of the inductive component of a probabilistic inference is reached. This proposal leads to vindicating the view that typical predictive probabilistic inferences by enumeration and analogy are (...)
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  • Bayesian conditionalization and probability kinematics.Colin Howson & Allan Franklin - 1994 - British Journal for the Philosophy of Science 45 (2):451-466.
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  • Is there a Bayesian justification of hypothetico‐deductive inference?Samir Okasha & Karim Thébault - 2020 - Noûs 54 (4):774-794.
    Many philosophers have claimed that Bayesianism can provide a simple justification for hypothetico-deductive inference, long regarded as a cornerstone of the scientific method. Following up a remark of van Fraassen, we analyze a problem for the putative Bayesian justification of H-D inference in the case where what we learn from observation is logically stronger than what our theory implies. Firstly, we demonstrate that in such cases the simple Bayesian justification does not necessarily apply. Secondly, we identify a set of sufficient (...)
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  • Components of probabilistic support: The two-proposition case.P. T. Landsberg & J. Wise - 1988 - Philosophy of Science 55 (3):402-414.
    Support functions $s(h,e)=p(h\backslash e)-p(h)$ are widely used in discussion of explanation, causality and, recently, in connection with the possibility or otherwise of probabilistic induction. With this latter application in view, a rather complete analysis of the variety of support functions, their interrelationships and their "non-deductive" and "inductive" components is presented. With the restriction to two propositions, three variable probabilities are enough to discuss such problems. The analysis is illustrated by graphs, a Venn diagram and by using the Laplace Rule of (...)
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  • The plurality of bayesian measures of confirmation and the problem of measure sensitivity.Branden Fitelson - 1999 - Philosophy of Science 66 (3):378.
    Contemporary Bayesian confirmation theorists measure degree of (incremental) confirmation using a variety of non-equivalent relevance measures. As a result, a great many of the arguments surrounding quantitative Bayesian confirmation theory are implicitly sensitive to choice of measure of confirmation. Such arguments are enthymematic, since they tacitly presuppose that certain relevance measures should be used (for various purposes) rather than other relevance measures that have been proposed and defended in the philosophical literature. I present a survey of this pervasive class of (...)
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  • (1 other version)Probabilité et support inductif. Sur le thèoréme de Popper-Miller.Guillaume Rochefort-Maranda - 2004 - Dialogue 43 (3):499-526.
    In 1983, in an open letter to the journal Nature, Karl Popper and David Miller set forth a particularly strong critical argument which sought to demonstrate the impossibility of inductive probability. Since its publication the argument has faced many criticisms and we argue in this article that they do not reach their objectives. We will first reconstruct the demonstration made by Popper and Miller in their initial article and then try to evaluate the main arguments against it. Although it is (...)
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  • (1 other version)Probabilité et support inductif. Sur le théorème de Popper-Miller.Guillaume Rochefort-Maranda - 2004 - Dialogue 43 (3):499-526.
    In 1983, in an open letter to the journal Nature, Karl Popper and David Miller set forth a particularly strong critical argument which sought to demonstrate the impossibility of inductive probability. Since its publication the argument has faced many criticisms and we argue in this article that they do not reach their objectives. We will first reconstruct the demonstration made by Popper and Miller in their initial article and then try to evaluate the main arguments against it. Although it is (...)
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  • An interchange on the Popper-Miller argument.Charles S. Chihara & Donald A. Gillies - 1988 - Philosophical Studies 54 (1):1 - 8.
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  • Some further reflections on the Popper-Miller 'disproof' of probabilistic induction.Colin Howson - 1990 - Australasian Journal of Philosophy 68 (2):221 – 228.
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  • Wofür sprechen die daten?Thomas Bartelborth - 2004 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 35 (1):13-40.
    What Do the Data Tell Us? Justification of scientific theories is a three-place relation between data, theories, and background knowledge. Though this should be a commonplace, many methodologies in science neglect it. The article will elucidate the significance and function of our background knowledge in epistemic justification and their consequences for different scientific methodologies. It is argued that there is no simple and at the same time acceptable statistical algorithm that justifies a given theory merely on the basis of certain (...)
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  • Partly deductive support in the Popper-Miller argument.Burke Townsend - 1989 - Philosophy of Science 56 (3):490-496.
    Popper and Miller (1983) have presented an argument purporting to establish the impossibility of inductive probability. Here I discuss critically their characterization of a deductive part of nondeductive support, a point that has not figured centrally in previous responses.
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  • One wave or three? A problem for realism.Neil A. Sheldon - 1985 - British Journal for the Philosophy of Science 36 (4):431-436.
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  • A bayesian analysis of excess content and the localisation of support.Colin Howson & Allan Franklin - 1985 - British Journal for the Philosophy of Science 36 (4):425-431.
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  • A reinstatement, in response to Gillies, of Redhead's argument in support of induction.I. J. Good - 1987 - Philosophy of Science 54 (3):470-472.
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  • In defense of the Popper-Miller argument.Donald Gillies - 1986 - Philosophy of Science 53 (1):110-113.
    In their 1983 article, Popper and Miller present an argument against inductive probability. This argument is criticized by Redhead in his 1985 article. The aim of the present note is to state one form of the Popper-Miller argument, and defend it against Redhead's criticisms.
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  • Metaconfirmation.Denis Zwirn & Herv� P. Zwirn - 1996 - Theory and Decision 41 (3):195-228.
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  • Logique inductive et soutien probabiliste.Denis Zwirn & Hervé Zwirn - 1993 - Dialogue 32 (2):293-.
    Karl Popper et David Miller ont soutenu l'idée selon laquelle le soutien probabiliste positif = p − p > 0) que e apporte á h, lorsque de h on déduit e, ne justifie en rien l'espoir de pouvoir construire une logique inductive fondée sur le calcul des probabilityés.
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  • Confirmation and the ordinal equivalence thesis.Olav Benjamin Vassend - 2017 - Synthese:1-17.
    According to a widespread but implicit thesis in Bayesian confirmation theory, two confirmation measures are considered equivalent if they are ordinally equivalent—call this the “ordinal equivalence thesis”. I argue that adopting OET has significant costs. First, adopting OET renders one incapable of determining whether a piece of evidence substantially favors one hypothesis over another. Second, OET must be rejected if merely ordinal conclusions are to be drawn from the expected value of a confirmation measure. Furthermore, several arguments and applications of (...)
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  • Confirmation and the ordinal equivalence thesis.Olav B. Vassend - 2019 - Synthese 196 (3):1079-1095.
    According to a widespread but implicit thesis in Bayesian confirmation theory, two confirmation measures are considered equivalent if they are ordinally equivalent—call this the “ordinal equivalence thesis” (OET). I argue that adopting OET has significant costs. First, adopting OET renders one incapable of determining whether a piece of evidence substantially favors one hypothesis over another. Second, OET must be rejected if merely ordinal conclusions are to be drawn from the expected value of a confirmation measure. Furthermore, several arguments and applications (...)
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  • State of the field: Measuring information and confirmation.Vincenzo Crupi & Katya Tentori - 2014 - Studies in History and Philosophy of Science Part A 47 (C):81-90.
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