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  1. Précis of statistical significance: Rationale, validity, and utility.Siu L. Chow - 1998 - Behavioral and Brain Sciences 21 (2):169-194.
    The null-hypothesis significance-test procedure (NHSTP) is defended in the context of the theory-corroboration experiment, as well as the following contrasts: (a) substantive hypotheses versus statistical hypotheses, (b) theory corroboration versus statistical hypothesis testing, (c) theoretical inference versus statistical decision, (d) experiments versus nonexperimental studies, and (e) theory corroboration versus treatment assessment. The null hypothesis can be true because it is the hypothesis that errors are randomly distributed in data. Moreover, the null hypothesis is never used as a categorical proposition. Statistical (...)
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  • The structure of empirical knowledge.Laurence BonJour - 1985 - Cambridge, Mass.: Harvard University Press.
    1 Knowledge and Justification This book is an investigation of one central problem which arises in the attempt to give a philosophical account of empirical ...
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  • Hierarchy versus holism: A structuralist view on general relativity. [REVIEW]Thomas Bartelborth - 1993 - Erkenntnis 39 (3):383 - 412.
    The philosophical debate whether the epistemological and conceptual structure of science is better characterized as hierarchical or as holistic cannot be decideda priori. A case study on general relativity should help to clarify our representation of this section of physics. For this purpose Sneed's model-theoretic approach is used to reconstruct the structure of relativity. The proposed axiomatization of general relativity takes into account approximations and utilizes local models for a realistic view on the functioning of the theory. A central objective (...)
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  • Explanatory Unification.Thomas Bartelborth - 2002 - Synthese 130 (1):91-108.
    Explanations contribute to our understanding of the world byembedding phenomena into general nomic patterns that we recognize in the world. Manyof these patterns are, of course, causal ones, but the declaration as ``causal'' often fails to determinethe explanatory power of the pattern. More important is the systematization capacity and the empiricalcontent of the pattern or theory with respect to explanations. We can specify these parameters moreprecisely within the framework of the structuralist view of theories.
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  • Begründungsstrategien: Ein Weg Durch Die Analytische Erkenntnistheorie.Thomas Bartelborth - 1996 - De Gruyter.
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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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  • Fact, Fiction, and Forecast.Nelson Goodman - 1965 - Cambridge, Mass.: Harvard University Press.
    In his new foreword to this edition, Hilary Putnam forcefully rejects these nativist claims.
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  • The Design Argument.Elliott Sober - 2019 - Cambridge University Press.
    This Element analyzes the various forms that design arguments for the existence of God can take, but the main focus is on two such arguments. The first concerns the complex adaptive features that organisms have. Creationists who advance this argument contend that evolution by natural selection cannot be the right explanation. The second design argument - the argument from fine-tuning - begins with the fact that life could not exist in our universe if the constants found in the laws of (...)
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  • Explanation, invariance, and intervention.James Woodward - 1997 - Philosophy of Science 64 (4):41.
    This paper defends a counterfactual account of explanation, according to which successful explanation requires tracing patterns of counterfactual dependence of a special sort, involving what I call active counterfactuals. Explanations having this feature must appeal to generalizations that are invariant--stable under certain sorts of changes. These ideas are illustrated by examples drawn from physics and econometrics.
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  • Ασλωτοσ.A. M. Woodward - 1932 - The Classical Review 46 (01):9-11.
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  • Venetian sea levels, british bread prices, and the principle of the common cause.Elliott Sober - 2001 - British Journal for the Philosophy of Science 52 (2):331-346.
    When two causally independent processes each have a quantity that increases monotonically (either deterministically or in probabilistic expectation), the two quantities will be correlated, thus providing a counterexample to Reichenbach's principle of the common cause. Several philosophers have denied this, but I argue that their efforts to save the principle are unsuccessful. Still, one salvage attempt does suggest a weaker principle that avoids the initial counterexample. However, even this weakened principle is mistaken, as can be seen by exploring the concepts (...)
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  • The design argument.Elliott Sober - 2004 - In William Mann (ed.), The Blackwell Guide to the Philosophy of Religion. Oxford, UK: Blackwell. pp. 117–147.
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  • Normische gesetzeshypothesen und die wissenschaftsphilosophische bedeutung Des nichtmonotonen schliessens.Gerhard Schurz - 2001 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 32 (1):65-107.
    Normic Laws and the Significance of Nonmonotonic Reasoning for Philosophy of Science. Normic laws have the form ‘if A then normally B’. They have been discovered in the explanation debate, but were considered as empirically vacuous (§1). I argue that the prototypical (or ideal) normality of normic laws implies statistical normality (§2), whence normic laws have empirical content. In §3–4 I explain why reasoning from normic laws is nonmonotonic, and why the understanding of the individual case is so important here. (...)
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  • A fuzzy measure for explanatory coherence.Daniel Schoch - 2000 - Synthese 122 (3):291-311.
    In a series of articles, Paul Thagard has developed a connectionist''s modelfor the evaluation of explanatory coherence for competing systems ofhypotheses. He has successfully applied it to various examples from thehistory of science and common language reasoning. However, I will argue thathis formalism does not adequately represent explanatory relations betweenmore than two propositions.In this paper, I develop a generalization of Thagard''s approach. It is notsubject to the connectionist paradigm of neural nets, but is based on fuzzylogic: Explanatory coherence increases with (...)
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  • 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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  • On the impossibility of inductive probability.Michael Redhead - 1985 - British Journal for the Philosophy of Science 36 (2):185-191.
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  • The Grand Leap. [REVIEW]Paul Humphreys & David Freedman - 1996 - British Journal for the Philosophy of Science 47 (1):113-123.
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  • The white shoe is a red Herring.I. J. Good - 1966 - British Journal for the Philosophy of Science 17 (4):322.
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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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  • Are there algorithms that discover causal structure?David Freedman & Paul Humphreys - 1999 - Synthese 121 (1-2):29-54.
    There have been many efforts to infer causation from association byusing statistical models. Algorithms for automating this processare a more recent innovation. In Humphreys and Freedman[(1996) British Journal for the Philosophy of Science 47, 113–123] we showed that one such approach, by Spirtes et al., was fatally flawed. Here we put our arguments in a broader context and reply to Korb and Wallace [(1997) British Journal for thePhilosophy of Science 48, 543–553] and to Spirtes et al.[(1997) British Journal for the (...)
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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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  • Bayes or Bust?: A Critical Examination of Bayesian Confirmation Theory.John Earman - 1992 - MIT Press.
    There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes’s original paper to contemporary formal learning theory.In (...)
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  • Causality.Judea Pearl - 2000 - New York: Cambridge University Press.
    Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections (...)
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  • Reconstructing The Past: Parsimony, Evolution, and Inference.Elliott Sober - 1988 - MIT Press.
    Reconstructing the Past seeks to clarify and help resolve the vexing methodological issues that arise when biologists try to answer such questions as whether human beings are more closely related to chimps than they are to gorillas. It explores the case for considering the philosophical idea of simplicity/parsimony as a useful principle for evaluating taxonomic theories of evolutionary relationships. For the past two decades, evolutionists have been vigorously debating the appropriate methods that should be used in systematics, the field that (...)
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  • [Book Chapter].P. Thagard & C. P. Shelley - 1997
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  • Bayes or Bust?: A Critical Examination of Bayesian Confirmation Theory.John Earman - 1992 - Bradford.
    There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. (...)
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  • Scientific Method: A Historical and Philosophical Introduction.Barry Gower - 1996 - New York: Routledge.
    The central theme running throughout this outstanding new survey is the nature of the philosophical debate created by modern science's foundation in experimental and mathematical method. More recently, recognition that reasoning in science is probabilistic generated intense debate about whether and how it should be constrained so as to ensure the practical certainty of the conclusions drawn. These debates brought to light issues of a philosophical nature which form the core of many scientific controversies today. _Scientific Method: A Historical and (...)
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  • Fact, Fiction, and Forecast.Nelson Goodman - 1955 - Philosophy 31 (118):268-269.
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