Consider the following linear regression model, wherey is an n by 1 vector of observations on the dependent variable, X is an n row and 2 column matrix and epsilon is a residual n by 1 vector. B = B2 y = XB + E, You know that the value / that minimizes lly - XBl|2 is a minimum if Select one: O a. The eigenvalues of 2(X X) are all negative O b. The eigenvalues of Xy are all positive. O c. The eigenvalues of 2(X X) are all positive O d. The eigenvalues of X are all negative. O e. The eigenvalues of X are all positiveConsider the following linear regression model, where y is an n by 1 vector of observations on the dependent variable, X is an n row and 2 column matrix and epsilon is a residual n by 1 vector. B = B 2 y = XB+ e, The exact (i.e., the analytical solution) estimates of 1 and 2 that minimize lly - XBll2 Select one: Oa. B = 2XT X O b. B = 2 XT XXTy O c. B = 2XTy O d. B =- 2XTy + 2Xx O e. B = ( X X ) -1 xTyWhich of the following statements is correct? Select one: 0 a. If we know the MLE of the parameter 0 of a distribution, then we do not know the MLE of 62, we must calculate it from scratch. O b. If we know the MLE of the parameter 0 of a distribution, then we know the MLE of 62 O c. If we know the MLE of the parameter 0 of a distribution, then we know the MLE of any other parameter of that distribution without having to compute it