Negative 1 squared is just 1. And over here you have Y. And instead of just writing plus the expected value of negative Y, that's the same thing as minus the expected value of Y. So you have that and then all of that squared. Now notice, this is the exact same thing by definition as the variance of Y. So we just showed you just now, so this is the variance of Y. So we just showed you that the variance of the difference of two independent random variables is equal to the sum of the variances.