So I took some screen captures from the Khan Academy exercise on correlation coefficient intuition, and they've given us some correlation coefficients, and we need to match them to the various scatter plots. On that exercise, there's a little interface where we can drag these around in a table to match them to the different scatter plots. And the point isn't to figure out how exactly to calculate these. We'll do that in the future, but really to get an intuition of what we're trying to measure. And the main idea is that correlation coefficients are trying to measure how well a linear model can describe the relationship between two variables. So for example, if I have, let me draw, let me do some coordinate axes here. So let's say that's one variable.