The sales manager of a large automotive parts distributor wants to estimate the total annual sales for each ofthe company's regions. Five factors appear to be related to regional sales: the number of retail outlets in the region, the number of automobiles in the region registered as of April 1, the total personal income recorded in the first quarter of the year, the average age of the automobiles (years), and the number of sales supervisors in the region. The data for each region were gathered for last year. For example, see the following table. In region 1 there were 1,739 retail outlets stocking the company's automotive parts, there were 9,270,000 registered automobiles in the region as of April 1. and so on. The region's sales for that year were $37,702.000. Number of Annual Sales ($ Number of Automobiles Personal Income Average Age o'F Number of millions), Retail Outlets, Registered ($ billions), Automobiles SupervisorsJ 3! x1 (millions), x2 X3 (year's), X4 x5 37.792 1,739 9.27 85.4 3.5 9.9 24.196 1,221 5.85 58.7 5.9 5.0 32.955 1,845 8.81 68.1 4.4 7.0 3.611 129 3.81 29.2 4.9 5.9 17.625 1,895 18.31 33.8 3.5 7.0 45.919 2,296 1.1.62 95.1 4.1 13.0 29.693 1,687 8.96 69.3 4.1 15.9 8.114 241 6.28 16.3 5.9 11.9 26.116 649 7.77 34.9 5.5 16.6 12.994 1,427 1.9.92 15.1 4.1 18.0 cl. Conduct a test of hypothesis on each of the independent variables. Would you consider eliminating "outlets" and "bosses"? Use the 0.05 significance level. [Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.) 9 Answer is complete but not entirely correct. _o oz4o>o- 0-8on