I think now is as good a time as any to play around a little bit with the formula for variance and see where it goes. And I think just by doing this, we'll also get a little bit better intuition of just manipulating sigma notation or even what it means. So we learned several times that the formula for variance, and let's just do variance of a population. It's almost the same thing as variance of a sample. You just divide by n instead of n minus 1. Variance of a population is equal to, when you take each of the data points, x sub i, you subtract from that the mean, you square it, and then you take the average of all of these. So you add the squared distance for each of these points from i equals 1 to i is equal to n, and you divide it by n. So let's see what happens if we can, I don't know, maybe we want to multiply out the squared term and see where it takes us.