Major
Psychology
Research Abstract
How does considering alternative possibilities affect models of what causes changes in statistics? We manipulated two independent variables—prior estimation (whether participants estimated the most recent statistic prior to receiving the correct statistic), and counterfactual thinking (whether participants provided explanations for changes in the statistic in the opposite direction). We measured the following effects: 1) surprise about the correct statistic, 2) changes in participants’ causal models, 3) actions participants recommended to improve the statistic in coming years, and 4) estimates of how much the statistic could improve if proposed actions were implemented.
Faculty Mentor/Advisor
Edward Munnich
Included in
How Base Rate Statistics and Counterfactuals Influence Causal Models and Recommendations for Traffic Safety
How does considering alternative possibilities affect models of what causes changes in statistics? We manipulated two independent variables—prior estimation (whether participants estimated the most recent statistic prior to receiving the correct statistic), and counterfactual thinking (whether participants provided explanations for changes in the statistic in the opposite direction). We measured the following effects: 1) surprise about the correct statistic, 2) changes in participants’ causal models, 3) actions participants recommended to improve the statistic in coming years, and 4) estimates of how much the statistic could improve if proposed actions were implemented.
