The problem facing a manager is to assess the impact of factors on full-time (FT) job growth. Specically, 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 $millions), and the fulltime voluntary turnover (%). Use the accompanying data to complete parts (a) through (d) below. Click the icon to view the data table. a. State the multiple regression equation. Let X1 represent the Tota Worldwide Revenues ($millions) and let X2 represent the FT Voluntary Turnover (%). VI = + X\" + X2i (Round the constant and XZi-ooefcient to the nearest integer as needed. Round the X1i-ooefcient to four decimal places as needed.) Data of best companies to work for FT Total Worldwide Voluntary Total FT Revenues Turnover Jobs Added ($millions) (%) 2,035 74,000.000 8.281 7,082 11,700.000 9.603 326 4,150.000 11.294 1,357 27,706.772 3.346 1,654 10,960.000 15.644 130 1,445.977 2.888 1,160 3,651.328 6.168 - 207 2,321.000 5.844 281 382.000 11.221 355 317.586 15.533 716 2,331.041 8.335 238 3,700.000 14.821\f