Please answer part b in the picture. AlsoPlot the residuals vs the time periodic Compute the Durbin-Watson statistic. At the 0.05 level of significance, is there evidence of positive autocorrelation...

Please answer part b in the picture. Also Plot the residuals vs the time periodic Compute the Durbin-Watson statistic. At the 0.05 level of significance, is there evidence of positive autocorrelation among the residuals. D= Find the critical values of the Durbin Watson statistic dL= dU= Is there evidence of a positive autocorrelation among the residuals? based on the results of the last two questions is there a reason to question the validity of the model? what conclusions can you reach concerning the relationship between daily sales and atmospheric temperature? A) no conclusions can be reached because the model may not be valid B) as the atmospheric temperature increases the daily sales increase C) according to the model atmospheric temperature has no effect on the daily sales D) as atmospheric temperature decreases the daily sales increase

Extracted text: The owners of a chain of ice cream stores have the business objective of improving the forecast of daily sales so that staffing shortages can be minimized during the summer season. As a starting point, the owners decide to develop a simple linear regression model to predict daily sales based on atmospheric temperature. They select a sample of 15 consecutive days. The results are shown in the accompanying table. Complete parts (a) through (f) below. E Click the icon to view the data table. Click the icon to view a table of critical values of the Durbin-Watson statistic. a. Assuming a linear relationship, use the least-squares method to compute the regression coefficients b, and b,. - X Ice cream sales b, = - 2.7630 (Round to four decimal places as needed.) b, = 0.0637 (Round to four decimal places as needed.) Day Sales ($1,000) Temperature (°F) b. Predict the sales for a day in which the temperature is 87°F. 1.52 63 2 1.68 71 Y (87) = $ (Round to the nearest whole number as needed.) 3 1.92 75 4. 1.79 74 2.02 76 6. 2.36 81 2.16 81 8. 2.69 84 88 2.91 10 3.17 90 11 3.02 90 12 3.27 93 13 3.42 99 14 2.84 88 15 2.54 83