A health analyst studied the relationship between blood pressure and independent variables age (years), weight (kg.), body mass index and a stress index. Regressing weight against all other independent variables produced the output shown below. In checking for the presence of multicollinearity, what can the analyst conclude? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.952959719 0.908132226 0.890907018 2.389667816 20 Observations No evidence of multicollinearity

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A health analyst studied the relationship between blood pressure and independent
variables age (years), weight (kg.), body mass index and a stress index. Regressing
weight against all other independent variables produced the output shown below. In
checking for the presence of multicollinearity, what can the analyst conclude?
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
0.952959719
0.908132226
0.890907018
2.389667816
20
Observations
No evidence of multicollinearity
Evidence of multicollinearity
Statistics in this table do not allow us to make any conclusion about the
presence or absence of multicollinearity
Transcribed Image Text:A health analyst studied the relationship between blood pressure and independent variables age (years), weight (kg.), body mass index and a stress index. Regressing weight against all other independent variables produced the output shown below. In checking for the presence of multicollinearity, what can the analyst conclude? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.952959719 0.908132226 0.890907018 2.389667816 20 Observations No evidence of multicollinearity Evidence of multicollinearity Statistics in this table do not allow us to make any conclusion about the presence or absence of multicollinearity
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