So we are always in a concave upwards situation. Concave upwards means that our graph might look something like that. Actually, I don't want to draw a little squiggle, it might look something like that, and you see the reason why the second derivative implies concave upwards, a second derivative positive means that our derivative is constantly increasing, so the derivative is constantly increasing, it's negative, less negative, even less negative, let me do that in a different color. You see it's negative, less negative, even less negative, zero, positive, more positive, so it's increasing over the entire place. So if you have a critical point where the derivative is equal to zero, so the slope is equal to zero, and it's concave upwards, you see pretty clearly that we have minimized the function. So what is y going to be equal to? We actually don't even have to figure out what y has to be equal to in order to minimize the sum of squares, we could just put it back into this, but just for fun, we see that y would be negative 16 over x, so y would be equal to negative 4, and we could just figure out now what our sum of squares is.