Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Bayesian Statistics | 2 |
| Experiments | 2 |
| Foreign Countries | 2 |
| Probability | 2 |
| Stimuli | 2 |
| Associative Learning | 1 |
| Classification | 1 |
| College Students | 1 |
| Context Effect | 1 |
| Cues | 1 |
| Decision Making | 1 |
| More ▼ | |
Author
| Brown, Scott D. | 1 |
| Craig, Stewart | 1 |
| Hawkins, Guy | 1 |
| Lewandowsky, Stephan | 1 |
| Little, Daniel R. | 1 |
| Steyvers, Mark | 1 |
| Wagenmakers, Eric-Jan | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
| Australia | 2 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
Craig, Stewart; Lewandowsky, Stephan; Little, Daniel R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2011
The assumption in some current theories of probabilistic categorization is that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report 2 probabilistic-categorization experiments in which we investigated error…
Descriptors: Evidence, Feedback (Response), Associative Learning, Classification

Peer reviewed
Direct link
