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.

Total FT Jobs Added Total Worldwide Revenues FT Voluntary Turnover -72 871.800 15.677 -64 4487.000 8.322 223 746.000 12.064 608 1000.420 27.308 -53 2238.927 6.492 492 2600.000 5.673 1264 3050.195 16.188 -2 731.000 10.655 716 2331.041 8.335 71 608.200 5.790 21 276.616 6.375 498 6671.684 4.260 -67 3691.728 12.764 -2 2312.000 4.401 -129 31600.000 8.535 -237 5955.676 4.285 59 1498.124 2.784 94 2029.893 2.000 -111 23420.000 14.355 -128 1931.000 7.853

State the multiple regression equation.Let

X1

represent the Total Worldwide Revenues ($millions) and let

X2

represent the FT Voluntary Turnover (%).

Yi=enter your response here+enter your response hereX1i+enter your response hereX2i

(Round the constant and

X2i-coefficient

to the nearest integer as needed. Round the

X1i-coefficient

to four decimal places as needed.)