Now, note what happens as you move across the chart. States farther to the right have higher rates of mask use. And as mask use increases, the frequency of observed covid-19 symptoms decreases: More masks, less covid-19.
This relationship is called a correlation, and it’s a strikingly tight one. Often in these types of plots you have to squint really hard to suss out such a relationship, and researchers occasionally go to comical lengths to divine the presence of a correlation where none really exists.
But there’s no need for that here. There’s a simple statistical measure of correlation intensity called “R-squared,” which goes from zero (absolutely no relationship between the two variables) to 1 (the variables move perfectly in tandem). The R-squared of CovidCast’s mask and symptom data is 0.73, meaning that you can predict about 73 percent of the variability in state-level covid-19 symptom prevalence simply by knowing how often people wear their masks.
