Perceiving distributions

The events people experience strongly shape their decisions and attitudes. Experiencing extreme weather events is related to attitudes towards climate change (Hoffman et al. 2022), disasters affect the willingness to purchase insurance (Kamiya & Yanase, 2019), and investors may overweight rare extreme positive returns (Blau et al., 2020).

What people experience typically can be described to follow probability distributions: For instance, most of the time there is little or no strong precipitation, but there is a non-zero probability of extreme downpours and flooding. People should pay attention to these extreme events. But under which conditions do they weight them accurately and when do they over- or underweight them? This raises the more general question, how people represent the information they experience from such probability distributions.
The goal of this project is to assess how people represent the information they experience. In the real world, we rarely have control over the underlying distributions. Therefore, we will rely on a combination of experiments and computational models to understand how people represent information from various distributions to make judgments and decisions.