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 $millions), and the full-time voluntary turnover (%). Use the accompanying data to complete parts (a) through (d) below. BE Click the icon to view the data table. a. State the multiple regression equation. Let X, represent the Total Worldwide Revenues ($millions) and let X2 represent the FT Voluntary Turnover (%). Y, = +() X1:+ ()X21 (Round the constant and X2j-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 (%) - 237 5,955.676 4.285 1,264 3,050.195 16.188 - 16 380.941 11.827 569 1,309.239 6.996 178 3,900.000 5.990 55 280.000 7.688 - 111 23,420.000 14.355 492 2,600.000 5.673 1,264 12,316.379 20.038 326 4,150.000 11.294 494 6,332.446 16.986 228 25,364.000 5.617 1,357 27,706.772 3.346 238 3,700.000 14.821 1,003 3,949.000 16.123 237 1,556.000 3.402 842 14,778.000 4.611 36 551.000 12.383 223 746.000 12.064 373 8,657.000 9.030