A statistical program is recommended. You may need to use this table to answer this question.The following data show the daily closing prices (in dollars per share) for a stock.DateNov. 3Nov. 4Nov. 7Nov. 8Nov. 9Nov. 10Nov. 11Nov. 14Nov. 15Nov. 16Nov. 17Nov. 18Nov. 21Nov. 22Nov. 23Nov. 25Nov. 28Nov. 29Nov. 30Dec. 1Price ($)82.9582.9483.5783.1982.7583.9584.6084.3585.6286.5586.8387.8187.3687.9688.8188.7989.2089.1588.8889.14(a) Define the independent variable Period, where Period = 1 corresponds to the data for November 3, Period = 2 corresponds to the data forNovember 4, Period = 3 corresponds to the data for November 7, and so on. Develop the estimated regression equation that can be used topredict the closing price (in dollars per share) given the value of Period. Use x for Period. (Round your numerical values to two decimalplaces.)ŷ = (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, Period = 3 corresponds to the data for November 7, and soon. Develop the estimated regression equation that can be used to predict the closing price (in dollars per share) given the value of Period. Use x for Period. (Round your numerical values to two decimal places.)(b) At the 0.05 level of significance, test for any positive autocorrelation in the residuals of the regression model.State the null and alternative hypotheses.Ho: P = 0Ha: p<0Ho: P < 0Ha:p = 0Ho: p=0Ha:p>0Ho: P > 0Ha: p = 0Find the value of the test statistic. (Round your answer to two decimal places.)0.83What are the critical values? (Round your answers to two decimal places.)dL=duXYou may have reversed the order of division.X

the following data shows the daily closing prices (in dollars as per share) for stock.DatePriceNov,…

A statistical program is recommended. You may need to use this table to answer this question. The following data show the daily closing prices (in dollars per share) for a stock. Date Nov. 3 Nov. 4 Nov. 7 Nov. 8 Nov. 9 Nov. 10 Nov. 11 Nov. 14 Nov. 15 Nov. 16 Nov. 17 Nov. 18 Nov. 21 Nov. 22 Nov. 23 Nov. 25 Nov. 28 Nov. 29 Nov. 30 Dec. 1 Price ($) 82.95 82.94 83.57 83.19 82.75 83.95 84.60 84.35 85.62 86.55 86.83 87.81 87.36 87.96 88.81 88.79 89.20 89.15 88.88 89.14 (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, Period = 3 corresponds to the data for November 7, and so on. Develop the estimated regression equation that can be used to predict the closing price (in dollars per share) given the value of Period. Use x for Period. (Round your numerical values to two decimal places.) ŷ =