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Sarafoglou, Alexandra; van der Heijden, Anna; Draws, Tim; Cornelisse, Joran; Wagenmakers, Eric-Jan; Marsman, Maarten – Psychology Learning and Teaching, 2022
Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we…
Descriptors: Bayesian Statistics, Thinking Skills, Undergraduate Students, Psychology
Lu, Hongjing; Chen, Dawn; Holyoak, Keith J. – Psychological Review, 2012
How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy…
Descriptors: Inferences, Thinking Skills, Comparative Analysis, Models
Bowers, Jeffrey S.; Davis, Colin J. – Psychological Bulletin, 2012
According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak.…
Descriptors: Bayesian Statistics, Psychology, Brain, Theories
Gershman, Samuel J.; Blei, David M.; Niv, Yael – Psychological Review, 2010
A. Redish et al. (2007) proposed a reinforcement learning model of context-dependent learning and extinction in conditioning experiments, using the idea of "state classification" to categorize new observations into states. In the current article, the authors propose an interpretation of this idea in terms of normative statistical inference. They…
Descriptors: Conditioning, Statistical Inference, Inferences, Bayesian Statistics
Lee, Michael D.; Wagenmakers, Eric-Jan – Psychological Review, 2005
D. Trafimow presented an analysis of null hypothesis significance testing (NHST) using Bayes's theorem. Among other points, he concluded that NHST is logically invalid, but that logically valid Bayesian analyses are often not possible. The latter conclusion reflects a fundamental misunderstanding of the nature of Bayesian inference. This view…
Descriptors: Psychology, Statistical Inference, Statistical Significance, Bayesian Statistics
Lee, Michael D.; Wagenmakers, Eric-Jan – Psychological Review, 2005
This paper comments on the response offered by Trafimow on Lee and Wagenmakers comments on Trafimow's original article. It seems our comment should have made it clear that the objective Bayesian approach we advocate views probabilities neither as relative frequencies nor as belief states, but as degrees of plausibility assigned to propositions in…
Descriptors: Researchers, Probability, Statistical Inference, Bayesian Statistics