| Popis: |
Bayesian models that optimally integrate prior probabilities with observations have successfully explained many aspects of human cognition. Research on decision-making under risk, however, is usually done through laboratory tasks that attempt to remove the effect of prior knowledge on choice. We ran a large online experiment in which risky options paid out according to the distribution of Democratic and Republican voters in US congressional districts to test the effects of manipulating prior probabilities on participants’ choices. We find evidence that people’s risk preferences are appropriately influenced by prior probabilities, and discuss how the study of risky choice can be integrated into the Bayesian approach to studying cognition. |
