Abstract
In this period of global uncertainty, the public is being inundated by information (and misinformation) from news sources, social media, and the community about the spread of COVID-19 and disease more generally. Moreover, unlike with most widespread news coverage <https://time.com/5779872/coronavirus-ebola-news-coverage/> , data and models are being used to explain the story by news organizations, health organizations, and governments. The reasons we are presently socially distancing are entrenched in an understanding of exponential growth and flattening the curve. A pair of survey experiments run on Ãptimus Analyticsâ Daily National Tracking Poll explores public statistical literacy by examining their ability to calculate and understand exponential growth. Our results present evidence suggesting that although individuals can face difficulty in calculating exponential growth, they do understand the nature of exponential relationships. These findings may be used to help better ground effective communication strategies aimed at the general public. Future research developing out of these initial survey results will continue to explore public understanding of exponential growth both domestically and abroad.
Highlights
As the medical community, governments, business, and the public come together to fight the COVID-19 pandemic, data scientists have a special role in helping to communicate what the data mean
Given the onslaught of statistical analyses presented to the public in the media, there is a clear question of how an understanding of exponential growth might influence an individual’s worry over COVID-19
Statistical models detail potential trajectories for disease spread. These models help to inform decision–makers on the scale and costs associated with fighting the spread of the virus- and present an overall picture of what is at stake. This has led to the current estimates of 5- or 6-digit deaths in the United States, which puts COVID-19 on track to be one of the leading causes of death in the United States in 2020
Summary
Governments, business, and the public come together to fight the COVID-19 pandemic, data scientists have a special role in helping to communicate what the data mean. As an initial investigation into testing statistical literacy among Americans with respect to exponential growth, a pair of survey experiments were tested over an 8-day time period These experiments aim to explore public understanding of both linear and exponential relationships applied to two different contexts—one related to the spread of disease and another using an alternative, lighter subject. We present the second survey experiment, which exposes respondents to a data visualization outlining various trends and asks them to choose which line best describes a growth situation presented to them Both questions in the survey are conducted by splittesting where half of the survey respondents are randomly assigned to linear growth treatment and the other half are assigned to the exponential growth treatment. We briefly explore future research avenues as follow-ups to this analysis
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