The basic least squares equations, that is, the first-order conditions for the minimization of the sum of squared residuals, that can be interpreted, when the solution exists, as the (minimized) residuals being orthogonal, or normal, to the matrix of regressors. The solution of the normal equations generates the least squares estimator .