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  1. Judgment Under Uncertainty: Heuristics and Biases.Daniel Kahneman, Paul Slovic & Amos Tversky (eds.) - 1982 - Cambridge University Press.
    The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important...
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  • Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment.Amos Tversky & Daniel Kahneman - 1983 - Psychological Review 90 (4):293-315.
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  • On narrow norms and vague heuristics: A reply to Kahneman and Tversky.Gerd Gigerenzer - 1996 - Psychological Review 103 (3):592-596.
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  • Probability, confirmation, and the conjunction fallacy.Crupi Vincenzo, Fitelson Branden & Tentori Katya - 2008 - Thinking and Reasoning 14 (2):182-199.
    The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt of providing a satisfactory account of the phenomenon has proven challenging. Here, we elaborate the suggestion (first discussed by Sides et al., 2001) that in standard conjunction problems the fallacious probability judgments experimentally observed are typically guided by sound assessments of confirmation relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal result is (...)
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  • Bayesian Epistemology.Luc Bovens & Stephan Hartmann - 2003 - Oxford: Oxford University Press. Edited by Stephan Hartmann.
    Probabilistic models have much to offer to philosophy. We continually receive information from a variety of sources: from our senses, from witnesses, from scientific instruments. When considering whether we should believe this information, we assess whether the sources are independent, how reliable they are, and how plausible and coherent the information is. Bovens and Hartmann provide a systematic Bayesian account of these features of reasoning. Simple Bayesian Networks allow us to model alternative assumptions about the nature of the information sources. (...)
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  • Testimony.Luc Bovens & Stephan Hartmann - 2003 - In Luc Bovens & Stephan Hartmann (eds.), Bayesian Epistemology. Oxford: Oxford University Press.
    Addresses ‘too-odd-not-to-be-true’ reasoning in the assessment of testimony. This is the curious phenomenon that an initially less plausible report from multiple independent witnesses may elicit more confidence than an initially more plausible report.
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  • Bayesian statistical inference in psychology: Comment on Trafimow (2003).Michael D. Lee & Eric-Jan Wagenmakers - 2005 - Psychological Review 112 (3):662-668.
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  • Walter the Banker: The Conjunction Fallacy Reconsidered. [REVIEW]Stephan Hartmann & Wouter Meijs - 2012 - Synthese 184 (1):73-87.
    In a famous experiment by Tversky and Kahneman (Psychol Rev 90:293–315, 1983), featuring Linda the bank teller, the participants assign a higher probability to a conjunction of propositions than to one of the conjuncts, thereby seemingly committing a probabilistic fallacy. In this paper, we discuss a slightly different example featuring someone named Walter, who also happens to work at a bank, and argue that, in this example, it is rational to assign a higher probability to the conjunction of suitably chosen (...)
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  • Theory of Probability.Harold Jeffreys - 1940 - Philosophy of Science 7 (2):263-264.
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  • Paul Slovic, and Amos Tversky, eds.Daniel Kahneman - 1982 - In Daniel Kahneman, Paul Slovic & Amos Tversky (eds.), Judgment Under Uncertainty: Heuristics and Biases. Cambridge University Press.
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  • The conjunction fallacy: a misunderstanding about conjunction?Daniel Osherson - 2004 - Cognitive Science 28 (3):467-477.
    It is easy to construct pairs of sentences X, Y that lead many people to ascribe higher probability to the conjunction X-and-Y than to the conjuncts X, Y. Whether an error is thereby committed depends on reasoners’ interpretation of the expressions “probability” and “and.” We report two experiments designed to clarify the normative status of typical responses to conjunction problems. © 2004 Cognitive Science Society, Inc. All rights reserved.
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  • The importance of proving the null.C. R. Gallistel - 2009 - Psychological Review 116 (2):439-453.
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  • The conjunction fallacy and the many meanings of and.Ralph Hertwig, Björn Benz & Stefan Krauss - 2008 - Cognition 108 (3):740-753.
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  • The conjunction fallacy: a misunderstanding about conjunction?K. Tentori - 2004 - Cognitive Science 28 (3):467-477.
    It is easy to construct pairs of sentences X, Y that lead many people to ascribe higher probability to the conjunction X‐and‐Y than to the conjuncts X, Y. Whether an error is thereby committed depends on reasoners' interpretation of the expressions “probability” and “and.” We report two experiments designed to clarify the normative status of typical responses to conjunction problems.
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  • Testing boundary conditions for the conjunction fallacy: Effects of response mode, conceptual focus, and problem type.Douglas H. Wedell & Rodrigo Moro - 2008 - Cognition 107 (1):105-136.
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  • Probability, confirmation, and the conjunction fallacy.Vincenzo Crupi, Branden Fitelson & Katya Tentori - 2007 - Thinking and Reasoning 14 (2):182 – 199.
    The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt to provide a satisfactory account of the phenomenon has proved challenging. Here we elaborate the suggestion (first discussed by Sides, Osherson, Bonini, & Viale, 2002) that in standard conjunction problems the fallacious probability judgements observed experimentally are typically guided by sound assessments of _confirmation_ relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal (...)
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  • How persuasive is a good fit? A comment on theory testing.Seth Roberts & Harold Pashler - 2000 - Psychological Review 107 (2):358-367.
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  • Argument Content and Argument Source: An Exploration.Ulrike Hahn, Adam J. L. Harris & Adam Corner - 2009 - Informal Logic 29 (4):337-367.
    Argumentation is pervasive in everyday life. Understanding what makes a strong argument is therefore of both theoretical and practical interest. One factor that seems intuitively important to the strength of an argument is the reliability of the source providing it. Whilst traditional approaches to argument evaluation are silent on this issue, the Bayesian approach to argumentation (Hahn & Oaksford, 2007) is able to capture important aspects of source reliability. In particular, the Bayesian approach predicts that argument content and source reliability (...)
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  • Differential weighting in integration theory.Gregg C. Oden & Norman H. Anderson - 1971 - Journal of Experimental Psychology 89 (1):152.
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  • Tversky, eds.D. Kahneman & P. Slovic - 1982 - In Daniel Kahneman, Paul Slovic & Amos Tversky (eds.), Judgment Under Uncertainty: Heuristics and Biases. Cambridge University Press.
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  • Abstraction is uncooperative.Jonathan E. Adler - 1984 - Journal for the Theory of Social Behaviour 14 (2):165–181.
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  • The conjunction fallacy.G. Wolford, H. Taylor & R. Beck - 1986 - Bulletin of the Psychonomic Society 24 (5):351-351.
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