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  1. Elementary probabilistic operations: a framework for probabilistic reasoning.Siegfried Macho & Thomas Ledermann - 2024 - Thinking and Reasoning 30 (2):259-300.
    The framework of elementary probabilistic operations (EPO) explains the structure of elementary probabilistic reasoning tasks as well as people’s performance on these tasks. The framework comprises three components: (a) Three types of probabilities: joint, marginal, and conditional probabilities; (b) three elementary probabilistic operations: combination, marginalization, and conditioning, and (c) quantitative inference schemas implementing the EPO. The formal part of the EPO framework is a computational level theory that provides a problem space representation and a classification of elementary probabilistic problems based (...)
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  • When Success Is Not Enough: The Symptom Base-Rate Can Influence Judgments of Effectiveness of a Successful Treatment.Fernando Blanco, María Manuela Moreno-Fernández & Helena Matute - 2020 - Frontiers in Psychology 11.
    Patients’ beliefs about the effectiveness of their treatments are key to the success of any intervention. However, since these beliefs are usually formed by sequentially accumulating evidence in the form of the covariation between the treatment use and the symptoms, it is not always easy to detect when a treatment is actually working. In Experiments 1 and 2, we presented participants with a contingency learning task in which a fictitious treatment was actually effective to reduce the symptoms of fictitious patients. (...)
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  • An Eye-Tracking Study of Statistical Reasoning With Tree Diagrams and 2 × 2 Tables.Georg Bruckmaier, Karin Binder, Stefan Krauss & Han-Min Kufner - 2019 - Frontiers in Psychology 10:436373.
    Changing the information format from probabilities into frequencies as well as employing appropriate visualizations such as tree diagrams or 2 × 2 tables are important tools that can facilitate people’s statistical reasoning. Previous studies have shown that despite their widespread use in statistical textbooks, both of those visualization types are only of restricted help when they are provided with probabilities, but that they can foster insight when presented with frequencies instead. In the present study, we attempt to replicate this effect (...)
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  • Are Jurors Intuitive Statisticians? Bayesian Causal Reasoning in Legal Contexts.Tamara Shengelia & David Lagnado - 2021 - Frontiers in Psychology 11.
    In criminal trials, evidence often involves a degree of uncertainty and decision-making includes moving from the initial presumption of innocence to inference about guilt based on that evidence. The jurors’ ability to combine evidence and make accurate intuitive probabilistic judgments underpins this process. Previous research has shown that errors in probabilistic reasoning can be explained by a misalignment of the evidence presented with the intuitive causal models that people construct. This has been explored in abstract and context-free situations. However, less (...)
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  • Processing Probability Information in Nonnumerical Settings – Teachers’ Bayesian and Non-bayesian Strategies During Diagnostic Judgment.Timo Leuders & Katharina Loibl - 2020 - Frontiers in Psychology 11.
    A diagnostic judgment of a teacher can be seen as an inference from manifest observable evidence on a student’s behavior to his or her latent traits. This can be described by a Bayesian model of in-ference: The teacher starts from a set of assumptions on the student (hypotheses), with subjective probabilities for each hypothesis (priors). Subsequently, he or she uses observed evidence (stu-dents’ responses to tasks) and knowledge on conditional probabilities of this evidence (likelihoods) to revise these assumptions. Many systematic (...)
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  • A New Visualization for Probabilistic Situations Containing Two Binary Events: The Frequency Net.Karin Binder, Stefan Krauss & Patrick Wiesner - 2020 - Frontiers in Psychology 11:506040.
    In teaching statistics in secondary schools and at university, two visualizations are primarily used when situations with two dichotomous characteristics are represented: 2×2 tables and tree diagrams. Both visualizations can be depicted either with probabilities or with frequencies. Visualizations with frequencies have been shown to help students significantly more in Bayesian reasoning problems than probability visualizations do. Because tree diagrams or double-trees (which are largely unknown in school) are node-branch-structures, these two visualizations (compared to the 2×2 table) can even simultaneously (...)
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  • Reference Dependence in Bayesian Reasoning: Value Selection Bias, Congruence Effects, and Response Prompt Sensitivity.Alaina Talboy & Sandra Schneider - 2022 - Frontiers in Psychology 13.
    This work examines the influence of reference dependence, including value selection bias and congruence effects, on diagnostic reasoning. Across two studies, we explored how dependence on the initial problem structure influences the ability to solve simplified precursors to the more traditional Bayesian reasoning problems. Analyses evaluated accuracy and types of response errors as a function of congruence between the problem presentation and question of interest, amount of information, need for computation, and individual differences in numerical abilities. Across all problem variations, (...)
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  • Evidencing How Experience and Problem Format Affect Probabilistic Reasoning Through Interaction Analysis.Manuele Reani, Alan Davies, Niels Peek & Caroline Jay - 2019 - Frontiers in Psychology 10.
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  • Why Can Only 24% Solve Bayesian Reasoning Problems in Natural Frequencies: Frequency Phobia in Spite of Probability Blindness.Patrick Weber, Karin Binder & Stefan Krauss - 2018 - Frontiers in Psychology 9:375246.
    For more than 20 years, research has proven the beneficial effect of natural frequencies when it comes to solving Bayesian reasoning tasks (Gigerenzer & Hoffrage, 1995). In a recent meta-analysis, McDowell & Jacobs (2017) showed that presenting a task in natural frequency format increases performance rates to 24% compared to only 4% when the same task is presented in probability format. Nevertheless, on average three quarters of participants in their meta-analysis failed to obtain the correct solution for such a task (...)
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  • Editorial: Improving Bayesian Reasoning: What Works and Why?David R. Mandel & Gorka Navarrete - 2015 - Frontiers in Psychology 6.
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