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 Smillions), and the full-time voluntary turnover (%). Use the accompanying data to complete parts (a) through (d) below. E Click the icon to view the data table. a. State the multiple regression equation. Let X, represent the Total Worldwide Revenues (Smillions) and let X, represent the FT Voluntary Turnover (%). (Round the constant and X-coefficient to the nearest integer as needed. Round the X-coefficient to four decimal places as needed.)

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Author:Amos Gilat
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1

Data of Best Companies to Work For
FT
Total Worldwide Voluntary
Total FT
Revenues
Turnover
($millions)
1,071.000
11,220.000
382.000
Jobs Added
(%)
249
15.064
- 224
5.032
281
11.221
460
33,000.000
4.763
- 19
686.000
9.721
2,402
24,400.000
11.673
161
373.693
5.400
888.000
10.837
- 207
2,321.000
3,024.095
9,502.000
2,470.720
9,374.000
34,163.000
5.844
75
2.806
60
4.908
523
6.471
- 122
6.802
309
0.000
252
860.815
10.310
95
706.757
10.535
11,700.000
3,700.000
46,100.000
31,600.000
7,082
9.603
238
14.821
207
5.728
- 129
8.535
-
Transcribed Image Text:Data of Best Companies to Work For FT Total Worldwide Voluntary Total FT Revenues Turnover ($millions) 1,071.000 11,220.000 382.000 Jobs Added (%) 249 15.064 - 224 5.032 281 11.221 460 33,000.000 4.763 - 19 686.000 9.721 2,402 24,400.000 11.673 161 373.693 5.400 888.000 10.837 - 207 2,321.000 3,024.095 9,502.000 2,470.720 9,374.000 34,163.000 5.844 75 2.806 60 4.908 523 6.471 - 122 6.802 309 0.000 252 860.815 10.310 95 706.757 10.535 11,700.000 3,700.000 46,100.000 31,600.000 7,082 9.603 238 14.821 207 5.728 - 129 8.535 -
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 X, represent the FT Voluntary Turnover (%).
OX1 + (DX21
=
+
i
(Round the constant and X2;-coefficient to the nearest integer as needed. Round the X4;-coefficient to four decimal places as needed.)
Transcribed Image Text: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 X, represent the FT Voluntary Turnover (%). OX1 + (DX21 = + i (Round the constant and X2;-coefficient to the nearest integer as needed. Round the X4;-coefficient to four decimal places as needed.)
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