Here’s an interesting correlation. As I was looking into factors confounding standardized testing results, I created a map (of Connecticut) displaying a student score indicator against the financial situation of the individual towns. The background is split by town area, and the shade of grey showcases the percentage of people under SNAP (Supplemental Nutrition Assistance Program)–this serves as an indicator for the financial situation of citizens by town (darker grey = more people receive aid in that region) . The bubbles are data from all public schools in Connecticut, showcasing the percentage of students in that school that scored over a set national benchmark (higher percent = better-performing student body = darker shade of orange) . Very evidently, the schools with poorer performing students bodies coincide almost perfectly with towns where a higher population receive food assistance.

I made this data in Tableau, sourcing my data from data.gov as well as data.ct.gov. I created the town line maps using documentation from UConn and polygon information from CT State Data Center . This was really the first time I had used Tableau, and it doesn’t seem too shabby (yay!).

Update: I wrote an op-ed on this.