Now, if you go to the next data point, two comma two, right over here, what happened? Well, the X variable was right on the mean. And because of that, that entire term became zero. The X Z score was zero. And so that would have taken away a little bit from our correlation coefficient. The reason why it would take away, even though it's not negative, you're not contributing to the sum, but you're going to be dividing by a slightly higher value by including that extra pair. If you had a data point where, let's say X was below the mean and Y was above the mean, something like this, if this was one of the points, this term would have been negative because the Y Z score would have been positive and the X Z score would have been negative.