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The Use of Visualizations to Improve Bayesian Reasoning: A Literature Review [PDF]
Vision, 2023 Decisions are often made under uncertainty. The most that one can do is use prior knowledge (e.g., base rates, prior probabilities, etc.) and make the most probable choice given the information we have.
Lucy Cui, Stephanie Lo, Zili Liu
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The Effects of Working Memory and Probability Format on Bayesian Reasoning [PDF]
Frontiers in Psychology, 2020 Bayesian reasoning is common and critical in everyday life while the performance on Bayesian reasoning is rather poor. Previous studies showed that people could enhance their performance by applying cognitive resources under the natural frequency format ...
Lin Yin +5 more
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Bayesian Reasoning with Trained Neural Networks [PDF]
Entropy, 2021 We showed how to use trained neural networks to perform Bayesian reasoning in order to solve tasks outside their initial scope. Deep generative models provide prior knowledge, and classification/regression networks impose constraints.
Jakob Knollmüller, Torsten A. Enßlin
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Indirect reciprocity with Bayesian reasoning and biases. [PDF]
PLoS Computational Biology, 2023 Reputations can foster cooperation by indirect reciprocity: if I am good to you then others will be good to me. But this mechanism for cooperation in one-shot interactions only works when people agree on who is good and who is bad.
Bryce Morsky +2 more
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The psychology of Bayesian reasoning [PDF]
Frontiers in Psychology, 2014 Most psychological research on Bayesian reasoning since the 1970s has used a type of problem that tests a certain kind of statistical reasoning performance. The subject is given statistical facts within a hypothetical scenario. Those facts include a base-rate statistic and one or two diagnostic probabilities.
David R. Mandel
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Bayesian reasoning with ifs and ands and ors [PDF]
Frontiers in Psychology, 2015 The Bayesian approach to the psychology of reasoning generalizes binary logic, extending the binary concept of consistency to that of coherence, and allowing the study of deductive reasoning from uncertain premises.
Nicole eCruz +3 more
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How to Train Novices in Bayesian Reasoning
Mathematics, 2022 Bayesian Reasoning is both a fundamental idea of probability and a key model in applied sciences for evaluating situations of uncertainty. Bayesian Reasoning may be defined as the dealing with, and understanding of, Bayesian situations.
Theresa Büchter +6 more
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Effect of Probability Information on Bayesian Reasoning: A Study of Event-Related Potentials [PDF]
Frontiers in Psychology, 2019 People often confront Bayesian reasoning problems and make decisions under uncertainty in daily life. However, the time course of Bayesian reasoning remains unclear.
Zifu Shi +4 more
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Measuring people’s covariational reasoning in Bayesian situations
Frontiers in Psychology, 2023 Previous research on Bayesian reasoning has typically investigated people’s ability to assess a posterior probability (i.e., a positive predictive value) based on prior knowledge (i.e., base rate, true-positive rate, and false-positive rate).
Nicole Steib +6 more
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Medical student syndrome: a bayesian reasoning failure [PDF]
BMC Medical EducationBackground Medical Student Syndrome (MSS) is often understood as a manifestation of illness anxiety disorder where medical students misinterpret benign symptoms as signs of a serious illness.
Ryan C. Clarkson, Naeem Paruk
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