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 (%) 314 3,319.000 18.283 - 72 871.800 15.677 207 46, 100.000 5.728 - 67 3,691.728 12.764 1,085 15,000.000 3.287 2,013 5,027.418 7.753 608 1,000.420 27.308 228 25,364.000 5.617 124 396. 196 10.076 523 2,470.720 6.471 55 280.000 7.688 498 6,671.684 4.260 - 53 2,238.927 6.492 - 106 10,900.000 3.856 - 111 23,420.000 14.355 249 1,071.000 15.064 1,886 20,729.000 7.451 2,402 24,400.000 11.673 238 3,700.000 14.821 4,040 21,396.000 13.136 Print Done