The following data show the daily closing prices (in dollars per share) for a stock. Date Price ($) Nov. 3 82.57 Nov. 4 82.40 Nov. 7 83.85 Nov. 8 82.24 Nov. 9 82.05 Nov. 10 82.70 Nov. 11 84.45 Nov. 14 84.77 Nov. 15 85.78 Nov. 16 86.57 Nov. 17 86.11 Nov. 18 87.62 Nov. 21 87.96 Nov. 22 87.80 Nov. 23 88.45 Nov. 25 89.09 Nov. 28 88.16 Nov. 29 88.28 Nov. 30 88.76 Dec. 1 88.02 a. Define the independent variable Period, where Period = 1 corresponds to the data for November 3, Period 2 corresponds to the data for November 4, and so on. Develop the estimated regression equation that can be used to predict the closing price given the value of Period (to 3 decimals). Price = + Period b. At the 0.05 level of significance, test for any positive autocorrelation in the data. What is the value of the Durbin-Watson statistic (to 3 decimals)? With critical values for the Durbin-Watson test for autocorrelation di = 1.2 and du = 1.41, what is your conclusion? - Select your