Probabilistic Interval Forecasts: An Individual Differences Approach to Understanding Forecast Communication

Abstract EN

Predictive interval forecasts, showing a range of values with specified probability, have the potential to improve decisions compared to point estimates.

The research reported here demonstrates that this advantage extends from college undergraduates to a wide user group and does not depend on education.

In two experiments, participants made decisions based on predictive intervals or point estimates and answered questions about them.

In Experiment 1, they also completed numeracy and working memory span tests.

Those using predictive intervals were better able to identify situations requiring precautionary action.

Nonetheless, two errors were noted: (1) misinterpreting predictive intervals as diurnal fluctuation (deterministic construal errors) and (2) judging the probability of events within and beyond the interval, when asked about them separately, as greater than 100%.

These errors were only partially explained by WMS and numeracy.

Importantly, omitting visualizations eliminated deterministic construal errors and overestimation of percent chance was not consistently related to decision quality.

Thus, there may be important benefits to predictive interval forecasts that are not dependent on a full understanding of the theoretical principles underlying them or an advanced education, making them appropriate for a broad range of users with diverse backgrounds, weather concerns, and risk tolerances.