Click on the validation icon to see the significance of the correlation between the X and Y Topics using a controlled multi-variable regression.

Click VERIFY to run the validation and REMOVE REGRESSION to revert back to a simple trend line.

Even if there is a strong apparent relationship in the Scatterplot, this could be misleading. The trend could be due to several factors:

There could be a third factor that actually affects both the X and Y Topics. In this case, X and Y would appear to be related only because they are both related to the other factor. For instance, places with low education also have a lot of people using food stamps, but using food stamps does not lead to poor education, or vice versa - instead, both affect (or are affected by) income.
X and Y could actually be two sides of the same coin. For instance, unemployment and average hours worked may appear to have a strong relationship, only because they both reflect economic conditions - people who are unemployed work fewer hours.
The relationship could be purely random chance. This happens when viewing a small number of places in the scatterplot (under 50 or so), but is unlikely when looking at hundreds or thousands of places.
There could actually be a true relationship between X and Y, where one contributes to the other.

Create a Scatterplot