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Hsu, Anne S.; Horng, Andy; Griffiths, Thomas L.; Chater, Nick – Cognitive Science, 2017
Identifying patterns in the world requires noticing not only unusual occurrences, but also unusual absences. We examined how people learn from absences, manipulating the extent to which an absence is expected. People can make two types of inferences from the absence of an event: either the event is possible but has not yet occurred, or the event…
Descriptors: Statistical Inference, Bayesian Statistics, Evidence, Prediction
Taylor, Eric G.; Ahn, Woo-kyoung – Cognitive Psychology, 2012
Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C…
Descriptors: Evidence, Prior Learning, Bayesian Statistics, Correlation
Hawkins, Guy; Brown, Scott D.; Steyvers, Mark; Wagenmakers, Eric-Jan – Cognitive Science, 2012
For decisions between many alternatives, the benchmark result is Hick's Law: that response time increases log-linearly with the number of choice alternatives. Even when Hick's Law is observed for response times, divergent results have been observed for error rates--sometimes error rates increase with the number of choice alternatives, and…
Descriptors: Bayesian Statistics, Reaction Time, Context Effect, Decision Making
Craigmile, Peter F.; Peruggia, Mario; Van Zandt, Trisha – Psychometrika, 2010
Human response time (RT) data are widely used in experimental psychology to evaluate theories of mental processing. Typically, the data constitute the times taken by a subject to react to a succession of stimuli under varying experimental conditions. Because of the sequential nature of the experiments there are trends (due to learning, fatigue,…
Descriptors: Reaction Time, Models, Experimental Psychology, Stimuli
Cook, Claire; Goodman, Noah D.; Schulz, Laura E. – Cognition, 2011
Probabilistic models of expected information gain require integrating prior knowledge about causal hypotheses with knowledge about possible actions that might generate data relevant to those hypotheses. Here we looked at whether preschoolers (mean: 54 months) recognize "action possibilities" (affordances) in the environment that allow them to…
Descriptors: Evidence, Play, Prior Learning, Hypothesis Testing
Kaplan, David – Society for Research on Educational Effectiveness, 2010
In recent years, attention in the education community has focused on the need for evidenced-based research, particularly educational policies and interventions that rest on "scientifically based research". The emphasis on scientifically based research in education has led to a corresponding increase in studies designed to provide strong warrants…
Descriptors: Evidence, Educational Research, Educational Policy, Models
Frank, Michael C.; Slemmer, Jonathan A.; Marcus, Gary F.; Johnson, Scott P. – Developmental Science, 2009
By 7 months of age, infants are able to learn rules based on the abstract relationships between stimuli ( Marcus et al., 1999 ), but they are better able to do so when exposed to speech than to some other classes of stimuli. In the current experiments we ask whether multimodal stimulus information will aid younger infants in identifying abstract…
Descriptors: Cues, Infants, Experiments, Learning Modalities
Maraun, Michael; Gabriel, Stephanie – Psychological Methods, 2010
In his article, "An Alternative to Null-Hypothesis Significance Tests," Killeen (2005) urged the discipline to abandon the practice of "p[subscript obs]"-based null hypothesis testing and to quantify the signal-to-noise characteristics of experimental outcomes with replication probabilities. He described the coefficient that he…
Descriptors: Hypothesis Testing, Statistical Inference, Probability, Statistical Significance
Rouder, Jeffrey N.; Yue, Yu; Speckman, Paul L.; Pratte, Michael S.; Province, Jordan M. – Psychological Review, 2010
A dominant theme in modeling human perceptual judgments is that sensory neural activity is summed or integrated until a critical bound is reached. Such models predict that, in general, the shape of response time distributions change across conditions, although in practice, this shape change may be subtle. An alternative view is that response time…
Descriptors: Reaction Time, Decision Making, Models, Statistical Analysis
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
Lamberts, Koen; Kent, Christopher – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2008
The time course of perception and retrieval of object features was investigated. Participants completed a perceptual matching task and 2 recognition tasks under time pressure. The recognition tasks imposed different retention loads. A stochastic model of feature sampling with a Bayesian decision component was used to estimate the rate of feature…
Descriptors: Memory, Language Processing, Bayesian Statistics, Recognition (Psychology)
Corner, Adam; Hahn, Ulrike – Journal of Experimental Psychology: Applied, 2009
Public debates about socioscientific issues are increasingly prevalent, but the public response to messages about, for example, climate change, does not always seem to match the seriousness of the problem identified by scientists. Is there anything unique about appeals based on scientific evidence--do people evaluate science and nonscience…
Descriptors: Bayesian Statistics, Climate, Experiments, Persuasive Discourse
Stahl, Christoph; Klauer, Karl Christoph – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2008
The distinction between verbatim and gist memory traces has furthered the understanding of numerous phenomena in various fields, such as false memory research, research on reasoning and decision making, and cognitive development. To measure verbatim and gist memory empirically, an experimental paradigm and multinomial measurement model has been…
Descriptors: Models, Memory, Bayesian Statistics, Cognitive Processes
Goodman, Noah D.; Tenenbaum, Joshua B.; Feldman, Jacob; Griffiths, Thomas L. – Cognitive Science, 2008
This article proposes a new model of human concept learning that provides a rational analysis of learning feature-based concepts. This model is built upon Bayesian inference for a grammatically structured hypothesis space--a concept language of logical rules. This article compares the model predictions to human generalization judgments in several…
Descriptors: Mathematics Education, Concept Formation, Models, Prediction
Zhang, Junni L.; Rubin, Donald B. – Journal of Educational and Behavioral Statistics, 2003
The topic of "truncation by death" in randomized experiments arises in many fields, such as medicine, economics and education. Traditional approaches addressing this issue ignore the fact that the outcome after the truncation is neither "censored" nor "missing," but should be treated as being defined on an extended sample space. Using an…
Descriptors: Experiments, Predictor Variables, Bayesian Statistics, Death
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