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Suppose You Are Interested in Estimating the Regression: Y =

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Suppose you are interested in estimating the regression: Y = β0 + β1X1 + β2X2 + β3X3.Using a sample of 40 observations,we get y = 13.2 + 18.4x1 + 0.033x2 + 1732.4x3,R2 = 0.88,s Suppose you are interested in estimating the regression: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub>.Using a sample of 40 observations,we get y = 13.2 + 18.4x<sub>1</sub> + 0.033x<sub>2</sub> + 1732.4x<sub>3</sub>,R<sup>2</sup> = 0.88,s   = 6) 3,s   = 15.2,s   = ) 0025,and s   = 1443.2.These results suggest that this model is affected by: A) autocorrelation. B) specification bias. C) multicollinearity. D) heteroscedasticity.
= 6) 3,s Suppose you are interested in estimating the regression: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub>.Using a sample of 40 observations,we get y = 13.2 + 18.4x<sub>1</sub> + 0.033x<sub>2</sub> + 1732.4x<sub>3</sub>,R<sup>2</sup> = 0.88,s   = 6) 3,s   = 15.2,s   = ) 0025,and s   = 1443.2.These results suggest that this model is affected by: A) autocorrelation. B) specification bias. C) multicollinearity. D) heteroscedasticity.
= 15.2,s Suppose you are interested in estimating the regression: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub>.Using a sample of 40 observations,we get y = 13.2 + 18.4x<sub>1</sub> + 0.033x<sub>2</sub> + 1732.4x<sub>3</sub>,R<sup>2</sup> = 0.88,s   = 6) 3,s   = 15.2,s   = ) 0025,and s   = 1443.2.These results suggest that this model is affected by: A) autocorrelation. B) specification bias. C) multicollinearity. D) heteroscedasticity.
= ) 0025,and s Suppose you are interested in estimating the regression: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub>.Using a sample of 40 observations,we get y = 13.2 + 18.4x<sub>1</sub> + 0.033x<sub>2</sub> + 1732.4x<sub>3</sub>,R<sup>2</sup> = 0.88,s   = 6) 3,s   = 15.2,s   = ) 0025,and s   = 1443.2.These results suggest that this model is affected by: A) autocorrelation. B) specification bias. C) multicollinearity. D) heteroscedasticity.
= 1443.2.These results suggest that this model is affected by:

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