The problem facing a manager is to assess the impact of factors on full-time {FT} job growth. Specifically. the manager is interest in the impact of total worldwide revenues and full-time voluntary turnover on the number of full-time jobs added in a year. Data were collected from a sample of 20 "best companies to work for." The data includes the total number of full-time jobs added in the past year, total worldwide revenue {in $millionsl. and the full-time voluntary turnover (to). Use the accompanying data to complete parts (a) through {d} below. @ Click the icon to view the data table. a. State the multiple regression equation. Let X1 represent the Total Worldwide Revenues i$millionsl and let X: represent the FT Voluntary Turnover (a). VI =D" D31\" {[1}le {Round the constant and Kai-coefcient to the nearest integer as needed. Round the mil-coefcient to four decimal places as needed.) X Data of Best Companies to Work For Total FT Total Worldwide FT Voluntary Jobs Added Revenues ($millions) Turnover (%) - 2 731.000 10.655 178 3,900.000 5.990 60 9,502.000 4.908 6,163 11,814.000 11.549 494 6,332.446 16.986 608 1,000.420 27.308 281 382.000 11.221 223 746.000 12.064 5 888.000 10.837 2,402 24,400.000 11.673 - 16 380.941 11.827 360 1,543.000 8.582 249 1,071.000 15.064 373 8,657.000 9.030 36 551.000 12.383 - 122 9,374.000 6.802 309 34, 163.000 0.000 460 33,000.000 4.763 842 14,778.000 4.611 86 696.200 5.233 Print Done