Explain the multiple regression on variables

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Analysis the following Question based on this situation. You run standard multiple regression on your variables (dependent Q; independents A, B, C, and D). The resulting regression output is the following:

 

Coefficients

Standard Error

P-value (or sig value)

Lower 95%

Upper 95%

Intercept

50.971

1.273

4.094E-06

524.04117

1091.796

A

-0.625

0.061

4.341E-11

-5.9751292

-4.09374

B

0.175

0.020

5.737E-05

2.7893473

6.931397

C

0.555

0.044

4.292E-03

0.1129530

0.543153

D

-0.0009

0.035

2.384E-08

0.0064627

0.010948

Based on the P-value, what conclusion can be withdrawn about independent variables A, B, C, and D?

a.) All independent variables have a significant predictive contribution to the model

b.) None of the independent variables has a significant predictive contribution to the model 

c.) Independent variable A has the least significant predictive contribution to the model

d.) Independent variable C has the most significant predictive contribution to the model 

Reference no: EM133170397

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