If we talk about the variance of the random variable X, that is the same thing as the expected value of the squared distances between our random variable X and its mean. And that right there, squared. So the expected value of these squared differences, and that is, you can also use the notation, sigma squared for the random variable X. This is just a review of things we already know, but I just want to reintroduce it, because I'll use this to build up some of our tools. So you do the same thing with this with random variable Y. The variance of random variable Y is the expected value of the squared difference between our random variable Y and the mean of Y, or the expected value of Y, squared. And that's the same thing as sigma squared of Y.