In this question we explore regression in a problem involving two attributes x and y. The dataset used for training contains four samples and is shown in Table 1. A second dataset containing two samples and shown in Table 2 is used for validation. Table 1: Training set. Table 2: Validation set. In Table 1, D1,D2,D3 and D4 represent the last four digits of your student ID ( D4 being the last, D2 the second last, etc). a) Let X be the design matrix obtained from the training dataset shown in Table 1 and w be the coefficients of the Minimum Mean Squared Error (MMSE) linear solution y ) =w0+w1. Furthermore, assume that. (XTX)1=[1.50.50.50.2] i) Obtain the MMSE coefficients w of the linear model y=w0+w1. Show all the steps involved in the calculation of w3 ii) Obtain the Mean Squared Error (MSE) of the linear solution that you have obtained, on both the training and validation sets