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  1. How to solve probability teasers.Maya Bar-Hillel - 1989 - Philosophy of Science 56 (2):348-358.
    Recently, Nathan (1986) criticized Bar-Hillel and Falk's (1982) analysis of some classical probability puzzles on the grounds that they wrongheadedly applied mathematics to the solving of problems suffering from "ambiguous informalities". Nathan's prescription for solving such problems boils down to assuring in advance that they are uniquely and formally soluble--though he says little about how this is to be done. Unfortunately, in real life problems seldom show concern as to whether their naturally occurring formulation is or is not ambiguous, does (...)
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  • How to solve probability teasers-discussion.Maya Bar-Hillel - 1989 - Philosophy of Science 56 (2):348-358.
    Recently, Nathan criticized Bar-Hillel and Falk's analysis of some classical probability puzzles on the grounds that they wrongheadedly applied mathematics to the solving of problems suffering from “ambiguous informalities”. Nathan's prescription for solving such problems boils down to assuring in advance that they are uniquely and formally soluble—though he says little about how this is to be done. Unfortunately, in real life problems seldom show concern as to whether their naturally occurring formulation is or is not ambiguous, does or does (...)
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  • Biased information and the exchange paradox.Anubav Vasudevan - 2019 - Synthese 196 (6):2455-2485.
    This paper presents a new solution to the well-known exchange paradox, or what is sometimes referred to as the two-envelope paradox. Many recent commentators have analyzed the paradox in terms of the agent’s biased concern for the contents of his own arbitrarily chosen envelope, claiming that such bias violates the manifest symmetry of the situation. Such analyses, however, fail to make clear exactly how the symmetry of the situation is violated by the agent’s hypothetical conclusion that he ought to switch (...)
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  • Advancing the rationality debate.Keith E. Stanovich & Richard F. West - 2000 - Behavioral and Brain Sciences 23 (5):701-717.
    In this response, we clarify several misunderstandings of the understanding/acceptance principle and defend our specific operationalization of that principle. We reiterate the importance of addressing the problem of rational task construal and we elaborate the notion of computational limitations contained in our target article. Our concept of thinking dispositions as variable intentional-level styles of epistemic and behavioral regulation is explained, as is its relation to the rationality debate. Many of the suggestions of the commentators for elaborating two-process models are easily (...)
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  • Intuitive reasoning about probability: Theoretical and experimental analyses of the “problem of three prisoners”.Shinsuke Shimojo & Shin'Ichi Ichikawa - 1989 - Cognition 32 (1):1-24.
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  • A subjective interpretation of conditional probability.Glenn Shafer - 1983 - Journal of Philosophical Logic 12 (4):453 - 466.
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  • The Hazards of Underspecified Models: The Case of Symmetry in Everyday Predictions.Peter Sedlmeier & Berna Kilinç - 2004 - Psychological Review 111 (3):770-780.
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  • On the use and misuse of the “Two Children” brainteaser.Mel D. Rutherford - 2010 - Pragmatics and Cognition 18 (1):165-174.
    Cognitive scientists employ brainteasers, or “cognitive illusions” in service of cognitive research. In some cases, rewording or paraphrasing a question can change the correct answer, without the experimenter realizing. In recent published articles describing cognitive research, participants have pondered brainteasers, including what is here called the “Two Children” problem. Although many accounts of this problem in the academic literature navigate its nuances correctly, in the popular press it is usually presented such that the wording of the question does not actually (...)
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  • Conditionalization and total knowledge.Ian Pratt-Hartmann - 2008 - Journal of Applied Non-Classical Logics 18 (2-3):247-266.
    This paper employs epistemic logic to investigate the philosophical foundations of Bayesian updating in belief revision. By Bayesian updating, we understand the tenet that an agent's degrees of belief—assumed to be encoded as a probability distribution—should be revised by conditionalization on the agent's total knowledge up to that time. A familiar argument, based on the construction of a diachronic Dutch book, purports to show that Bayesian updating is the only rational belief-revision policy. We investigate the conditions under which the premises (...)
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  • Probability and Direct Reference: Three Puzzles of Probability Theory: The Problem of the Two Boys, Freund's Problem and the Problem of the Three Prisoners.Martine Nida-Rümelin - 1993 - Erkenntnis 39 (1):51 - 78.
    I discuss three puzzles of probability theory which seem connected with problems of direct reference and rigid designation. The resolution of at least one of them requires referential use of definite descriptions in probability statements. I argue that contrary to common opinion all these puzzles are in a way still unsolved: They seem to exemplify cases in which a change of probabilities is rationally required, even though any specific change presupposes unjustified assumptions.
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  • Bertrand's chord, Buffon's needle, and the concept of randomness.Raymond Nickerson - 2005 - Thinking and Reasoning 11 (1):67 – 96.
    Two old problems in probability theory involving the concept of randomness are considered. Data obtained with one of them--Bertrand's chord problem--demonstrate the equivocality of this term in the absence of a definition or explication of assumptions underlying its use. They also support two propositions about probabilistic thinking: (1) upon obtaining an answer to a question of probability, people tend to see it as the answer, overlooking tacit assumptions on which it may be based, and tend not to consider the possibility (...)
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  • Perspectives on the 2 × 2 Matrix: Solving Semantically Distinct Problems Based on a Shared Structure of Binary Contingencies. [REVIEW]Hansjörg Neth, Nico Gradwohl, Dirk Streeb, Daniel A. Keim & Wolfgang Gaissmaier - 2021 - Frontiers in Psychology 11.
    Cognition is both empowered and limited by representations. The matrix lens model explicates tasks that are based on frequency counts, conditional probabilities, and binary contingencies in a general fashion. Based on a structural analysis of such tasks, the model links several problems and semantic domains and provides a new perspective on representational accounts of cognition that recognizes representational isomorphs as opportunities, rather than as problems. The shared structural construct of a 2 × 2 matrix supports a set of generic tasks (...)
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  • How not to solve it.Amos Nathan - 1986 - Philosophy of Science 53 (1):114-119.
    Six recently discussed problems in discrete probabilistic sample space, which have been found puzzling and even paradoxical, are reexamined. The importance is stressed of a sharp distinction between the formalization of mathematical problems and their formal solution that, applied to probability theory, must lead through the explicit partitioning of a sample space. If this approach is consistently followed, such problems reveal themselves to be either inherently ambiguous, and therefore without solution, or quite straightforward. In both cases nothing remains of any (...)
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  • A reply to Rapoport.L. Marinoff - 1996 - Theory and Decision 41 (2):157-164.
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  • On the importance of identifying the correct ‘problem space’.Gideon Keren - 1984 - Cognition 16 (2):121-128.
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  • Sleeping Beauty meets Monday.Karl Karlander & Levi Spectre - 2010 - Synthese 174 (3):397-412.
    The Sleeping Beauty problem—first presented by A. Elga in a philosophical context—has captured much attention. The problem, we contend, is more aptly regarded as a paradox: apparently, there are cases where one ought to change one’s credence in an event’s taking place even though one gains no new information or evidence, or alternatively, one ought to have a credence other than 1/2 in the outcome of a future coin toss even though one knows that the coin is fair. In this (...)
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  • On the study of statistical intuitions.Daniel Kahneman & Amos Tversky - 1982 - Cognition 11 (2):123-141.
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  • The psychology of dynamic probability judgment: order effect, normative theories, and experimental methodology.Jean Baratgin & Guy Politzer - 2007 - Mind and Society 6 (1):53-66.
    The Bayesian model is used in psychology as the reference for the study of dynamic probability judgment. The main limit induced by this model is that it confines the study of revision of degrees of belief to the sole situations of revision in which the universe is static (revising situations). However, it may happen that individuals have to revise their degrees of belief when the message they learn specifies a change of direction in the universe, which is considered as changing (...)
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  • What are conditional probabilities conditional upon?Keith Hutchison - 1999 - British Journal for the Philosophy of Science 50 (4):665-695.
    This paper rejects a traditional epistemic interpretation of conditional probability. Suppose some chance process produces outcomes X, Y,..., with probabilities P(X), P(Y),... If later observation reveals that outcome Y has in fact been achieved, then the probability of outcome X cannot normally be revised to P(X|Y) ['P&Y)/P(Y)]. This can only be done in exceptional circumstances - when more than just knowledge of Y-ness has been attained. The primary reason for this is that the weight of a piece of evidence varies (...)
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  • Auto-epistemology and updating.Matthias Hild - 1998 - Philosophical Studies 92 (3):321-361.
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  • Fuzziness of concepts and concepts of fuzziness.Gy Fuhrmann - 1988 - Synthese 75 (3):349 - 372.
    It has been a vexing question in recent years whether concepts are fuzzy. In this paper several views on the fuzziness of concepts are pointed out to have stemmed from dubious concepts of fuzziness. The underlying notions of the roles feasibly played byprototype, set, andprobability in modeling concepts strongly suggest that the controversy originates from a vague relation between intuitive and mathematical ideas in the cognitive sciences. It is argued that the application of fuzzy sets cannot resolve this vagueness since (...)
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  • When truisms clash: Coping with a counterintuitive problem concerning the notorious two-child family.Ruma Falk - 2011 - Thinking and Reasoning 17 (4):353 - 366.
    You know that a two-child family has a son. What is the probability that the family has two sons? And what is this probability if you know that the family has a son born on a Tuesday? The former question has been widely discussed previously. The latter adds a new puzzling twist to the situation. In both cases the answer should depend on the specifics of the assumed underlying procedure by which the given information has been obtained. Quantitative analysis, assuming (...)
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  • A closer look at the probabilities of the notorious three prisoners.Ruma Falk - 1992 - Cognition 43 (3):197-223.
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  • Conditionalization and not Knowing that One Knows.Aaron Bronfman - 2014 - Erkenntnis 79 (4):871-892.
    Bayesian Conditionalization is a widely used proposal for how to update one’s beliefs upon the receipt of new evidence. This is in part because of its attention to the totality of one’s evidence, which often includes facts about what one’s new evidence is and how one has come to have it. However, an increasingly popular position in epistemology holds that one may gain new evidence, construed as knowledge, without being in a position to know that one has gained this evidence. (...)
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  • Conditionalization and Belief De Se.Darren Bradley - 2010 - Dialectica 64 (2):247-250.
    Colin Howson (1995 ) offers a counter-example to the rule of conditionalization. I will argue that the counter-example doesn't hit its target. The problem is that Howson mis-describes the total evidence the agent has. In particular, Howson overlooks how the restriction that the agent learn 'E and nothing else' interacts with the de se evidence 'I have learnt E'.
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  • Battle in the planning office: Field experts versus normative statisticians.Marcel Boumans - 2008 - Social Epistemology 22 (4):389 – 404.
    Generally, rational decision-making is conceived as arriving at a decision by a correct application of the rules of logic and statistics. If not, the conclusions are called biased. After an impressive series of experiments and tests carried out in the last few decades, the view arose that rationality is tough for all, skilled field experts not excluded. A new type of planner's counsellor is called for: the normative statistician, the expert in reasoning with uncertainty par excellence. To unravel this view, (...)
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  • A commentary on Mel Rutherford’s ‘On the use and misuse of the “two children” brainteaser’.Maya Bar-Hillel - 2010 - Pragmatics and Cognition 18 (1):175-179.
    Rutherford criticizes the way some people have analyzed the 2-children problem, claiming that slight nuances in the problem’s formulation can change the correct answer. However, his own data demonstrate that even when there is a unique correct answer, participants give intuitive answers that differ from it systematically — replicating the data reported by those he criticizes. Thus, his critique reduces to an admonition to use care in formulating and analyzing this brainteaser — which is always a good idea — but (...)
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