The estimator of sigma squared (the random error’s variance) can be mathematically defined as: a. The diagonal of the hat matrix of the beta estimates b. The sum-of-squared errors divided by the quantity n less the number of estimated beta parameters c. The principal component eigenvalue of the error term.