Grocery retailer. A large, national grocery retailer tracks productivity and costs of its facilities closely. Data below were obtained from a single distribution center for a one-year period. Each data point for each variable represents one week of activity. The variables included are the number of cases shipped (X1), the indirect costs of the total labor hours as a percentage (X2), a qualitative predictor called holiday that is coded 1 if the week has a holiday and 0 otherwise (X3), and the total labor hours (Y). i: Xi1: Xi2: Xi3: Yi: 1 305,657 7.17 0 4264 2 328,476 6.20 0 4496 3 317,164 4.61 0 4317 ... ... ... ... ... 50 290,455 7.99 0 4499 51 411,750 7.83 0 4186 52 292,087 7.77 0 4342 a. Fit regression model (6.1) to the data using X1 and X2 only. b. Prepare an added-variable plot for each of the predictor variables X1 and X2. c. Do your plots in part (a) suggest that the regression relationships in the fitted regression function in part (a) are inappropriate for any of the predictor variables? Explain. d. Obtain the fitted regression function in part (a) by separately regressing both Y and X2 on X1, and then regressing the residuals in an appropriate fashion. (Kutner 414) Kutner, Michael. Applied Linear Regression Models-Revised Edtion, 4th Edition. McGraw-Hill Learning Solutions, 37994. VitalBook file. When there are two predictor variables X1 and X2, the regression model: Yi = 0 + 1Xi1 + 2Xi2 + i Model (6.1) (Kutner 215) Kutner, Michael. Applied Linear Regression Models-Revised Edtion, 4th Edition. McGraw-Hill Learning Solutions, 37994. VitalBook file