The Simple Linear Regression model is   Y = b0 + b1*X1 + u   and the Multiple Linear Regression model with k variables is:   Y = b0 + b1*X1 + b2*X2 + ... + bk*Xk + u   Y is the dependent variable, the X1, X2, ..., Xk are the explanatory variables, b0 is the intercept, b1, b2, ..., bk are the slope coefficients, and u is the error term,   Yhat represents the OLS fitted values, uhat represent the OLS residuals, b0_hat represents the OLS estimated intercept, and b1_hat, b2_hat,..., bk_hat, represent the OLS estimated slope coefficients. QUESTION 22 Suppose your estimated MLR model with two explanatory variables, X1 and log(X2), is: log(Y)_hat= 10 +0.5*X1 + 0.25*log(X2) Which of the following statements about the interpretation of the coefficient of log(X2) is correct? If X2 increases by 1%, Y is predicted to increase by approximately 25 units, holding X1 constant If X2 increases by 1%, Y is predicted to increase by approximately 0.25%, holding X1 constant If X2 increases by 1 unit, Y is predicted to increase by approximately 25%, holding X1 constant If X2 increases by 1 unit, Y is predicted to increase by approximately 0.25 units, holding X1 constant     QUESTION 23 Suppose your estimated MLR model is: Y_hat= 10 + 3*X + 12*D – 1.5*(X*D)  where X is a continuous variable, D is a dummy variable (i.e. taking only values 0 and 1), and X*D is the interaction term between the two variables. What is the predicted change in Y, if X goes up by 1 unit, given that D=1?   Y is predicted to increase by 12 units Y is predicted to decrease by 1.5 units Y is predicted to increase by 3 units Y is predicted to increase by 1.5 units     QUESTION 24 Suppose your estimated MLR model is: Y_hat= 10 + 3*X + 12*D – 1.5*(X*D)  where X is a continuous variable, D is a dummy variable (i.e. taking only values 0 and 1), and X*D is the interaction term between the two variables. What is the interpretation of the estimated coefficient associated with variable X?   It is the estimated effect of X on Y for D=1 It is the estimated effect of X on Y holding D constant It is the estimated effect of Y on X for D=1 It is the estimated effect of X on Y for D=0

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Question

The Simple Linear Regression model is

 

Y = b0 + b1*X1 + u

 

and the Multiple Linear Regression model with k variables is:

 

Y = b0 + b1*X1 + b2*X2 + ... + bk*Xk + u

 

Y is the dependent variable, the X1, X2, ..., Xk are the explanatory variables, b0 is the intercept, b1, b2, ..., bk are the slope coefficients, and u is the error term,

 

Yhat represents the OLS fitted values, uhat represent the OLS residuals, b0_hat represents the OLS estimated intercept, and b1_hat, b2_hat,..., bk_hat, represent the OLS estimated slope coefficients.

QUESTION 22

Suppose your estimated MLR model with two explanatory variables, X1 and log(X2), is:

log(Y)_hat= 10 +0.5*X1 + 0.25*log(X2)

Which of the following statements about the interpretation of the coefficient of log(X2) is correct?

  1. If X2 increases by 1%, Y is predicted to increase by approximately 25 units, holding X1 constant
  2. If X2 increases by 1%, Y is predicted to increase by approximately 0.25%, holding X1 constant
  3. If X2 increases by 1 unit, Y is predicted to increase by approximately 25%, holding X1 constant
  4. If X2 increases by 1 unit, Y is predicted to increase by approximately 0.25 units, holding X1 constant

 

 

QUESTION 23

Suppose your estimated MLR model is:

Y_hat= 10 + 3*X + 12*D – 1.5*(X*D) 

where X is a continuous variable, D is a dummy variable (i.e. taking only values 0 and 1), and X*D is the interaction term between the two variables. What is the predicted change in Y, if X goes up by 1 unit, given that D=1?

 

  1. Y is predicted to increase by 12 units
  2. Y is predicted to decrease by 1.5 units
  3. Y is predicted to increase by 3 units
  4. Y is predicted to increase by 1.5 units

 

 

QUESTION 24

Suppose your estimated MLR model is:

Y_hat= 10 + 3*X + 12*D – 1.5*(X*D) 

where X is a continuous variable, D is a dummy variable (i.e. taking only values 0 and 1), and X*D is the interaction term between the two variables. What is the interpretation of the estimated coefficient associated with variable X?

 

  1. It is the estimated effect of X on Y for D=1
  2. It is the estimated effect of X on Y holding D constant
  3. It is the estimated effect of Y on X for D=1
  4. It is the estimated effect of X on Y for D=0
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