Context

My girlfriend is a Statistics major, and one day she told me how in class her professor mentioned that the correlation coefficient (R^2) between two data sets is effectively pointless to use. When I asked her why, she described essentially the same idea behind this project: you can find data sets that happen to work well together that mathematically say they are "correlated," but logically don't make sense together. This is due to a "confounding variable," a variable that is directly correlated to two other variables that makes them seem like they are related to each other.