Randomly generate nine observations satisfying a normal linear model by taking xi ∼ N(50, 20) and yi = 45.0 + 0.1xi + ????i with ????i ∼ N(0, 1). Now add to the dataset a contaminated outlying observation 10 having x10 = 100, y10 = 100. Fit the normal linear model to the 10 observations using

(a) least squares,

(b) Huber’s M-estimation. Compare the model parameter estimates and the estimate of ????. Interpret.