Across multiple experiments, we found that Americans misestimated the growth of COVID-19 cases in the U.S. and that these estimates were in turn related to people’s forecasts of the duration of social distancing orders, and their own future adherence to these orders. We also investigated how mode of data presentation influences forecasting of future cases by showing participants data on the number of COVID-19 cases from a five-week period in either graphical or tabular form. We found that people shown tables produced more accurate forecasts compared to people shown line-graphs of the same data; yet, people shown line-graphs were more confident in their estimates. These findings suggest that graphs engender false-confidence in the accuracy of forecasts, that people’s forecasts of future cases may have important implications for their attitudes concerning social distancing, and that tables are better than graphs for informing the public about the trajectory of COVID-19.
Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm