Residual sum of squares in simple linear regression

For a nonconstant predictor, putThe minimized residual sum of squares isEach centered sum can be recovered in constant time from the five raw sums $\sum x_i$, $\sum y_i$, $\sum x_i^2$, $\sum x_i{y}_i$, and $\sum y_i^2$.