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.)
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.)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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1
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
-
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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