Here we're taking the distance between a point and what the model would have predicted. But we're squaring each of those residuals and adding them all up together. And just like we do with the sample standard deviation, we are now going to divide by one less than the number of residuals we just squared and added. So we have four residuals. We're gonna divide by four minus one, which is equal to, of course, three. You could view this part as a mean of the squared errors. And now we're gonna take the square root of it.