Fashion Bling operates a chain of 10 retail department stores. Each department store makes its own purchasing decisions. (Click the icon to view additional information.) Haulton decides to use simple regression analysis to examine whether one or more of three variables (the last three columns in the table) are cost drivers of purchasing department costs. Summary results for these regressions are as follows: (Click the icon to view the summary results.) Read the requirements. Requirement 1. Compare and evaluate the three simple regression models estimated by Haulton. Graph each one. We will begin by graphing each regression model. Start with plotting the regression model: PDC = a + (bxMPS). When drawing the regression line, use the highest and lowest values given for "MPS", then round the purchasing department costs to the nearest increment of $10,000 and merchandise purchased to the nearest million. (Enlarge the graph and use the line button displayed below to draw the graph.) Q Purchasing Department Costs (in 10,000's) xxxxxxxxx ixxxxxxxxx . . . 0 20 40 60 80 100 120 14050 Dollar value of Merchandise Purchased (in millions) Click to enlarge tranh More info - John Haulton, assistant to the president of Fashion Bling, is interested in better understanding the drivers of purchasing department costs. For many years, Fashion Bling has allocated purchasing department costs to products on the basis of the dollar value of merchandise purchased. A $100 item is allocated 10 times as many overhead costs associated with the purchasing department as a $10 item. Haulton recently attended a seminar titled "Cost Drivers in the Retail Industry." In a presentation at the seminar, Calico Fabrics, a leading competitor that has implemented activity-based costing, reported number of purchase orders and number of suppliers to be the two most important cost drivers of purchasing department costs. The dollar value of merchandise purchased in each purchase order was not found to be a significant cost driver. Haulton interviewed several members of the purchasing department at the Fashion Bling store in Miami. They believed that Calico Fabrics' conclusions also applied to their purchasing department. Haulton collects the following data for the most recent year for Fashion Bling's 10 retail department stores: A B Purchasing 1 Department Store Department Costs (PDC) Dollar Value of Merchandise Purchased (MP$) D Number of Purchase Orders (No. of POs) E Number of Suppliers (No. of Ss) 2 Baltimore $ 1,518,000 $ 68,285,000 4,362 137 3 Chicago 1,119,000 33,434,000 2,553 226 4 Los Angeles 556,000 121,250,000 1,426 13 5 Miami 2,041,000 118,910,000 5,941 196 6 New York 1,034,000 33,492,000 2,797 31 7 Phoenix 533,000 30,120,000 1,335 34 8 Seattle 1,542,000 103,010,000 7,579 115 9 St. Louis 1,746,000 38,025,000 3,600 130 10 Toronto 1,622,000 138,995,000 1,721 212 11 Vancouver 1,243,000 131,120,000 4,726 210 Print Done Data table Regression 1: PDC = a + (b x MP$) Variable Coefficient Standard Error t-Value Constant $ 1,041,311 $ Independent variable 1: MP$ 0.0031 2=0.08; Durbin-Watson statistic = 2.42 Regression 2: PDC = a + (b No. of POs) 341,346 3.05 0.0037 0.84 Variable Coefficient Standard Error t-Value Constant $ 735,118 $ 265,177 2.77 Independent variable 1: No. of POS $ 155.46 $ 64.66 2.40 =0.42; Durbin-Watson statistic = 1.99 Regression 3: PDC = a + (b No. of Ss) Variable Coefficient Standard Error t-Value Constant $ 774,664 $ 245,694 3.15 Independent variable 1: No. of Ss $ 3,993 $ 1,621 2.46 r = 0.43; Durbin-Watson statistic = 1.94 Requirements 1. Compare and evaluate the three simple regression models estimated by Haulton. Graph each one. 2. Do the regression results support the Calico Fabrics' presentation about the purchasing department's cost drivers? Which of these cost drivers would you recommend in designing an ABC system?