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THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION

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THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
An economist is in the process of developing a model to predict the price of gold.She believes that the two most important variables are the price of a barrel of oil (x1)and the interest rate (x2).She proposes the model y = β0 + β1x1 + β2x2 + β3x1x3 + ε.A random sample of 20 daily observations was taken.The computer output is shown below.
THE REGRESSION EQUATION IS
y = 115.6 + 22.3x1 + 14.7x2 - 1.36x1x2
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: An economist is in the process of developing a model to predict the price of gold.She believes that the two most important variables are the price of a barrel of oil (x<sub>1</sub>)and the interest rate (x<sub>2</sub>).She proposes the model 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>1</sub>x<sub>3</sub> + ε.A random sample of 20 daily observations was taken.The computer output is shown below. THE REGRESSION EQUATION IS y = 115.6 + 22.3x<sub>1</sub> + 14.7x<sub>2</sub> - 1.36x<sub>1</sub>x<sub>2</sub>     S = 20.9 R-Sq = 55.4% ANALYSIS OF VARIANCE    -Suppose that a regression relationship is given by Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + ε.If the simple linear regression of Y on X<sub>1</sub> is estimated from a sample of n observations,the resulting slope estimate will generally be biased for β<sub>1</sub>.But if the sample correlation between X<sub>1</sub> and X<sub>2</sub> is 0,the slope will not be biased for β<sub>1</sub>. How does X<sub>2</sub> affect β<sub>1</sub> if the sample correlation between X<sub>1</sub> and X<sub>2</sub> is zero?
S = 20.9 R-Sq = 55.4%
ANALYSIS OF VARIANCE
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: An economist is in the process of developing a model to predict the price of gold.She believes that the two most important variables are the price of a barrel of oil (x<sub>1</sub>)and the interest rate (x<sub>2</sub>).She proposes the model 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>1</sub>x<sub>3</sub> + ε.A random sample of 20 daily observations was taken.The computer output is shown below. THE REGRESSION EQUATION IS y = 115.6 + 22.3x<sub>1</sub> + 14.7x<sub>2</sub> - 1.36x<sub>1</sub>x<sub>2</sub>     S = 20.9 R-Sq = 55.4% ANALYSIS OF VARIANCE    -Suppose that a regression relationship is given by Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + ε.If the simple linear regression of Y on X<sub>1</sub> is estimated from a sample of n observations,the resulting slope estimate will generally be biased for β<sub>1</sub>.But if the sample correlation between X<sub>1</sub> and X<sub>2</sub> is 0,the slope will not be biased for β<sub>1</sub>. How does X<sub>2</sub> affect β<sub>1</sub> if the sample correlation between X<sub>1</sub> and X<sub>2</sub> is zero?
-Suppose that a regression relationship is given by Y = β0 + β1X1 + β2X2 + ε.If the simple linear regression of Y on X1 is estimated from a sample of n observations,the resulting slope estimate will generally be biased for β1.But if the sample correlation between X1 and X2 is 0,the slope will not be biased for β1.
How does X2 affect β1 if the sample correlation between X1 and X2 is zero?

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