We've actually already seen this, and I've actually shown you many, many videos ago when we first learned about it what this is. The covariance of a random variable with itself is really just the variance of that random variable. You could verify it for yourself. If you change this Y to an X, this becomes X minus the expected value of X times X minus the expected value of X, or that's the expected value of X minus the expected value of X squared. That's your definition of variance. Another way of thinking about the slope of our regression line, it can be literally viewed as the covariance of our two random variables over the variance of X. You can view it as the independent random variable.