Aduted R Square 70435 054.77825 011738 009497723 2360403 224520794 &P; 500 0 011

Question

Aduted R Square 70435 054.77825 011738 009497723 2360403 224520794 &P; 500 0 011896604 UMMARY OUTPUT atistics 0580134147 R Square Standard Emor 40 andard Eror Stat Intercep S&P; 500 Crude Oul Prices 0 001301139 008273488 014499817 0885499311 0 01688087 211797554 039604473 0 534781903 0 5960001070590665292 0. 0.486581852 SUMMARY OUTPUT sion Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0575697431 0331427532 031383352 0 046562751 40 Coefficients Standard Ermor Stat P-value Lower 95% Intercept Crude Oil Prices 0 0038285 0.007556146 050667368 0.615311302 -0.01146811 0 401374728 0.092477947 4 340221016 00001016410214162912

Explanation / Answer

D option

Multicollinearity refers to a situation in which two or more explanatory variables in a multiple regression model are highly linearly related. We have perfect multicollinearity if, for example as in the equation above, the correlation between two independent variables is equal to 1 or 1.

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