In-house restaurant dining is related to increases in COVID-19 cases: Illustrates correlation, regression, and good science reporting

Niv Elis, writing for The Hill, summarized a report created by JP Morgan analyst Jesse Edgerton. The report found a link between in-restaurant spending from three weeks ago and increases in new cases of COVID-19 in different states now. Data for the analysis came from 1) J.P. Morgan/Chase in-restaurant (not online/takeout) credit card purchases and 2) infection data from Johns Hopkins. 

How to use in class:

1. Correlation/regression: This graph, which summarizes the main findings from the report, may not include my beloved APA axis labels, but it does include an R2 and is a good example of a scatterplot. 

ALSO: The author of The Hill piece was careful to include this information from the study's author, which clarifies that correlation doesn't necessarily equal causation.

2) Creativity in data analysis: Often, in intro psych stats, we use examples rooted in traditional social science research. We should use such an example. But we MUST also use examples that demonstrate how data scientists can use the ENORMOUS data sets that are created by virtue of credit card usage, disease tracking, etc. in research. 

3) This is an example of good science reporting. This story was widely reported, but The Hill's coverage included the full graph and made sure to state that this relationship does not imply causality. 

4) Includes a video, and videos are a nice way to switch stuff up in class, aren't they?