Using results from the regression model, discuss whether you would have confidence in this multiple regression model to predict expected salary based on GPA, age, and gende

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Using results from the regression model, discuss whether you would have confidence in this multiple regression model to predict expected salary based on GPA, age, and gender?

SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
0.389395911
0.151629176
0.107747926
Standard Error
12.21174238
Observations
62
ANOVA
df
SS
MS
Significance F
Regression
1545.896129
515.2987096
3.455443432
0.022109834
Residual
58
8649.345807
149.1266518
Total
61
10195.24194
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
93.51214154
25.87757288
3.613636487
0.000632425
41.71255147
145.3117316
41.71255147
145.3117316
Age
-0.238577414
1.093820589
-0.218113845
0.828106007 -2.428097211
1.950942383
-2.428097211
1.950942383
GPA
-12.79023531
3.997425287
-3.199618353
0.002232046
-20.7919514 -4.788519224
-20.7919514
-4.788519224
Gender num
1.32088149
3.130832692
0.421894627
0.674661647
-4.94616105
7.587924029
-4.94616105
7.587924029
Transcribed Image Text:SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.389395911 0.151629176 0.107747926 Standard Error 12.21174238 Observations 62 ANOVA df SS MS Significance F Regression 1545.896129 515.2987096 3.455443432 0.022109834 Residual 58 8649.345807 149.1266518 Total 61 10195.24194 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 93.51214154 25.87757288 3.613636487 0.000632425 41.71255147 145.3117316 41.71255147 145.3117316 Age -0.238577414 1.093820589 -0.218113845 0.828106007 -2.428097211 1.950942383 -2.428097211 1.950942383 GPA -12.79023531 3.997425287 -3.199618353 0.002232046 -20.7919514 -4.788519224 -20.7919514 -4.788519224 Gender num 1.32088149 3.130832692 0.421894627 0.674661647 -4.94616105 7.587924029 -4.94616105 7.587924029
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