QUESTION 28 Suppose your estimated MLR model is: Y_hat = -30 + 2*X1 + 10*X2 Suppose the standard error for the estimated coefficient associated with X2 is equal to 5. Now, suppose that for some reason we multiply X2 by 5 and we re-estimate the model using the rescaled explanatory variable. What will be the value of the estimated coefficient of X2 and its standard error? The estimated coefficient of X2 will be equal to 50 and its standard error will be equal to 25. The estimated coefficient of X2 will be equal to 10 and its standard error will be equal to 5. The estimated coefficient of X2 will be equal to 2 and its standard error will be equal to 1. We cannot say based on the provided information. QUESTION 29 We have an MLR model with 2 explanatory variables, X1 and X2, where the standard deviations of these variables are 2 and 15, respectively. The estimated coefficients associated with X1 and X2 are 3 and 0.5, while their standard errors are 2 and 0.2, respectively. Which variable is more important in terms of 'economic significance'? X1 X2 They are of equal importance in terms of 'economic significance' We cannot say with the provided information QUESTION 30 We have an MLR model with 2 explanatory variables, X1 and X2, where the standard deviations of these variables are 2 and 15, respectively. The estimated coefficients associated with X1 and X2 are 3 and 0.5, while their standard errors are 2 and 0.2, respectively. Which variable is more important in terms of 'statistical significance'? X1 X2 They are of equal importance in terms of 'statistical significance' We cannot say
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 28
Suppose your estimated MLR model is:
Y_hat = -30 + 2*X1 + 10*X2
Suppose the standard error for the estimated coefficient associated with X2 is equal to 5.
Now, suppose that for some reason we multiply X2 by 5 and we re-estimate the model using the rescaled explanatory variable. What will be the value of the estimated coefficient of X2 and its standard error?
- The estimated coefficient of X2 will be equal to 50 and its standard error will be equal to 25.
- The estimated coefficient of X2 will be equal to 10 and its standard error will be equal to 5.
- The estimated coefficient of X2 will be equal to 2 and its standard error will be equal to 1.
- We cannot say based on the provided information.
QUESTION 29
We have an MLR model with 2 explanatory variables, X1 and X2, where the standard deviations of these variables are 2 and 15, respectively. The estimated coefficients associated with X1 and X2 are 3 and 0.5, while their standard errors are 2 and 0.2, respectively.
Which variable is more important in terms of 'economic significance'?
- X1
- X2
- They are of equal importance in terms of 'economic significance'
- We cannot say with the provided information
QUESTION 30
We have an MLR model with 2 explanatory variables, X1 and X2, where the standard deviations of these variables are 2 and 15, respectively. The estimated coefficients associated with X1 and X2 are 3 and 0.5, while their standard errors are 2 and 0.2, respectively.
Which variable is more important in terms of 'statistical significance'?
- X1
- X2
- They are of equal importance in terms of 'statistical significance'
- We cannot say with the provided information
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