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 $millions), and the full-time voluntary turnover (%). Use the accompanying data to complete parts (a) through (d) below. Click the icon to view the data table. a. State the multiple regression equation. Let X, represent the Total Worldwide Revenues ($millions) and let X2 represent the FT Voluntary Turnover (%). Y, = [+ () X1:+ (X21 (Round the constant and X2;-coefficient to the nearest integer as needed. Round the X1;-coefficient 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 (%) 460 33,000.000 4.763 2,402 24,400.000 11.673 6,368.000 11.451 - 111 23,420.000 14.355 - 16 380.941 11.827 94 2,029.893 2.000 36 551.000 12.383 75 3,024.095 2.806 193 1,144.000 5.351 -57 11,500.000 5.390 - 122 9,374.000 6.802 - 129 31,600.000 8.535 252 860.815 10.310 1,465 53,300.000 0.388 - 237 5,955.676 4.285 60 9,502.000 4.908 1,085 15,000.000 3.287 - 19 686.000 9.721 355 317.586 15.533 329 236.698 7.893 Print Done