Judgement Under Uncertainty: Heuristics and Biases, No. 1
| dc.contributor.author | Tversky, Amos | |
| dc.contributor.author | Kahneman, Daniel | |
| dc.date.accessioned | 2025-01-16T00:40:51Z | |
| dc.date.available | 2025-01-16T00:40:51Z | |
| dc.date.issued | 1973-07 | |
| dc.description | 36 pages | |
| dc.description.abstract | Most important decisions are based on beliefs concerning the likelihood of uncertain events such as the outcome of an election, the guilt of a defendant, or the future value of the dollar. These beliefs are usually expressed in statements such as "I think that ... ", "chances are ... ", "It is unlikely that .. . ", etc. Occasionally, beliefs concerning uncertain events are expressed in a numerical form as odds or subjective probabilities. What determines such beliefs? How do people assess the likelihood of an W1certain event or the value of an uncertain quantity? The theme of the present paper is that people rely on a limited number of heuristic principles by which they reduce the complex tasks of assessing likelihoods and predicting values to simpler judgmental operations. In general, these heuristics are quite useful, but sometimes they leads to severe and systematic errors. | |
| dc.identifier.uri | https://hdl.handle.net/1794/30344 | |
| dc.language.iso | en_US | |
| dc.publisher | Oregon Research Institute | |
| dc.rights | Creative Commons BY-NC-ND 4.0-US | |
| dc.subject | heuristics, judgement, likelihood, representativeness, availability | |
| dc.title | Judgement Under Uncertainty: Heuristics and Biases, No. 1 | |
| dc.type | Other |