The next 3 questions are also considered with optimization. You will use maximum likelihood (ML). Consider the simplest linear regression model where the dependent variable is only explained with a constant, Y = B + ej. Suppose you have a sample of n observations. Let's 1 e2 assume that the error term follows the normal distribution N (0, of ) with pdf given by Pr(e,; of) = expl . Find the ML VO22TI 202 estimator for B, B. An estimator is a formula. Hint: It is easiest to find the full log likelihood (see your notes on page 24) and then to maximize that function with respect to B and solve that equation for the unknown. Now assume that Yo takes on the values of 1, 2, 3, 4, 5. What is the value of the estimator (the estimate)? Type your numeric answer and submit