ReviewFrontiers in psychology2015
Comprehension and computation in Bayesian problem solving.
Review in Frontiers in psychology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Another chance for good reasoning.Psychonomic bulletin & review · 2017Trial
- Analyzing and supporting mental representations and strategies in solving Bayesian problems.Frontiers in psychology · 2026Article
- Effect of hit rate and cognitive style on Bayesian reasoning: evidence from eye movements.Frontiers in psychology · 2025Article
- How can we apply decision-making theories to wild animal behavior? Predictions arising from dual process theory and Bayesian decision theory.American journal of primatology · 2025Review
- The impact of problem domain on Bayesian inferences: A systematic investigation.Memory & cognition · 2024Article
- Previous beliefs affect Bayesian reasoning in conditions fostering gist comprehension.Memory & cognition · 2023Article
- Analyzing and supporting mental representations and strategies in solving Bayesian problems.Frontiers in psychology · 2023Article
- Reference Dependence in Bayesian Reasoning: Value Selection Bias, Congruence Effects, and Response Prompt Sensitivity.Frontiers in psychology · 2022Article
- Different Visualizations Cause Different Strategies When Dealing With Bayesian Situations.Frontiers in psychology · 2020Article
- Perspectives on the 2 × 2 Matrix: Solving Semantically Distinct Problems Based on a Shared Structure of Binary Contingencies.Frontiers in psychology · 2020Review
- Propensities and Second Order Uncertainty: A Modified Taxi Cab Problem.Frontiers in psychology · 2020Article
- From reading numbers to seeing ratios: a benefit of icons for risk comprehension.Psychological research · 2019Article
- How to Improve Performance in Bayesian Inference Tasks: A Comparison of Five Visualizations.Frontiers in psychology · 2019Article
- Effect of Probability Information on Bayesian Reasoning: A Study of Event-Related Potentials.Frontiers in psychology · 2019Article
- An Eye-Tracking Study of Statistical Reasoning With Tree Diagrams and 2 × 2 Tables.Frontiers in psychology · 2019Article
- Article
- Why Can Only 24% Solve Bayesian Reasoning Problems in Natural Frequencies: Frequency Phobia in Spite of Probability Blindness.Frontiers in psychology · 2018Article
- Structural mapping in statistical word problems: A relational reasoning approach to Bayesian inference.Psychonomic bulletin & review · 2017Article
- The Impact of Visualizing Nested Sets. An Empirical Study on Tree Diagrams and Unit Squares.Frontiers in psychology · 2016Article
- Toward an ecological analysis of Bayesian inferences: how task characteristics influence responses.Frontiers in psychology · 2015Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Humans have long been characterized as poor probabilistic reasoners when presented with explicit numerical information. Bayesian word problems provide a well-known example of this, where even highly educated and cognitively skilled individuals fail to adhere to mathematical norms. It is widely agreed that natural frequencies can facilitate Bayesian inferences relative to normalized formats (e.g., probabilities, percentages), both by clarifying logical set-subset relations and by simplifying numerical calculations. Nevertheless, between-study performance on "transparent" Bayesian problems varies widely, and generally remains rather unimpressive. We suggest there has been an over-focus on this representational facilitator (i.e., transparent problem structures) at the expense of the specific logical and numerical processing requirements and the corresponding individual abilities and skills necessary for providing Bayesian-like output given specific verbal and numerical input. We further suggest that understanding this task-individual pair could benefit from considerations from the literature on mathematical cognition, which emphasizes text comprehension and problem solving, along with contributions of online executive working memory, metacognitive regulation, and relevant stored knowledge and skills. We conclude by offering avenues for future research aimed at identifying the stages in problem solving at which correct vs. incorrect reasoners depart, and how individual differences might influence this time point.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.