Training Dept. of Nimrod Inc wants to develop a regression-based compensation model (compensation in $ per year, Comp) for its mid-level managers to encourage performance, loyalty, and continuing education based on three variables. ▪ Business unit-profitability (Profit per year in $). ▪ Working experiences in Nimrod Inc (Years). ▪ Whether or not a manager has a graduate degree (Grads). If a manager has a graduate degree equals 1, 0 otherwise. Table Attached Question: Interpret the coefficient of determination of the regression-based compensation model.

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Training Dept. of Nimrod Inc wants to develop a regression-based compensation model (compensation in $ per year, Comp) for its mid-level managers to encourage performance, loyalty, and continuing education based on three variables.

▪ Business unit-profitability (Profit per year in $).

▪ Working experiences in Nimrod Inc (Years).

▪ Whether or not a manager has a graduate degree (Grads). If a manager has a graduate degree equals 1, 0 otherwise.

Table Attached

Question:

Interpret the coefficient of determination of the regression-based compensation model.

Table 1. Data Collected for 36 Managers
Comp
Profit
Years
Grad
236.200
9.000.000
37
181.600
10.800.000
1
170.000
8.400.000
29
The following Table 2 shows the regression result.
Table 2. Regression Results.
Regression Statistics
Multiple R
0,916759383
R Square
0,840447766
Adjusted R Square
0,813855727
Standard Error
16888,68274
Observations
36
ANOVA
df
SS
MS
Significance F
Regression
5
4,5073E+10 9014686817 31,6052397
4,271E-11
Residual
30
8556828138
285227605
Total
35
5,363E+10
Coefficients
Standard Error
t Stat
P-value
Intercept
5354,378366
20815,993
0,25722426
0,798762
Profit
0,010315404
0,00183083
5,63427742
0,000004
Years
2455,373172
554,351395 4,42927211
0,000116
Grad
73310,27264
24595,2312
2,9806702
0,005658
Profit*grad
-0,000522662
0,00245843
-0,2126004
0,833077
Transcribed Image Text:Table 1. Data Collected for 36 Managers Comp Profit Years Grad 236.200 9.000.000 37 181.600 10.800.000 1 170.000 8.400.000 29 The following Table 2 shows the regression result. Table 2. Regression Results. Regression Statistics Multiple R 0,916759383 R Square 0,840447766 Adjusted R Square 0,813855727 Standard Error 16888,68274 Observations 36 ANOVA df SS MS Significance F Regression 5 4,5073E+10 9014686817 31,6052397 4,271E-11 Residual 30 8556828138 285227605 Total 35 5,363E+10 Coefficients Standard Error t Stat P-value Intercept 5354,378366 20815,993 0,25722426 0,798762 Profit 0,010315404 0,00183083 5,63427742 0,000004 Years 2455,373172 554,351395 4,42927211 0,000116 Grad 73310,27264 24595,2312 2,9806702 0,005658 Profit*grad -0,000522662 0,00245843 -0,2126004 0,833077
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