Informal Logic 24 (1):41-70 (2004)
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Abstract |
Bayesian reasoning has been applied formally to statistical inference, machine learning and analysing scientific method. Here I apply it informally to more common forms of inference, namely natural language arguments. I analyse a variety of traditional fallacies, deductive, inductive and causal, and find more merit in them than is generally acknowledged. Bayesian principles provide a framework for understanding ordinary arguments which is well worth developing
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Keywords | Bayesian reasoning, logical fallacies, statistical fallacies, causal fallacies, teaching probabilistic reasoning |
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References found in this work BETA
Judgment Under Uncertainty: Heuristics and Biases.Amos Tversky & Daniel Kahneman - 1974 - Science 185 (4157):1124-1131.
The Foundations of Mathematics and Other Logical Essays.Frank Plumpton Ramsey - 1925 - Routledge & Kegan Paul.
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Citations of this work BETA
A Normative Framework for Argument Quality: Argumentation Schemes with a Bayesian Foundation.Ulrike Hahn & Jos Hornikx - 2016 - Synthese 193 (6):1833-1873.
A Probabilistic Analysis of Argument Cogency.David Godden & Frank Zenker - 2018 - Synthese 195 (4):1715-1740.
Argument Content and Argument Source: An Exploration.Ulrike Hahn, Adam J. L. Harris & Adam Corner - 2009 - Informal Logic 29 (4):337-367.
Because Hitler Did It! Quantitative Tests of Bayesian Argumentation Using Ad Hominem.Adam J. L. Harris, Anne S. Hsu & Jens K. Madsen - 2012 - Thinking and Reasoning 18 (3):311 - 343.
Normative Theories of Argumentation: Are Some Norms Better Than Others?Adam Corner & Ulrike Hahn - 2013 - Synthese 190 (16):3579-3610.
View all 13 citations / Add more citations
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