a. Estimate a linear-log model. The model transforms the x-variable, but not the y-variable: Copy the equation with the estimated coefficients into your Word document.
b. Interpret the results. Remember that interpretation changes when we change the functional form.
c. Create a scatter plot that includes the fitted regression line.
d. Create a 99% interval estimate for the slope coefficient. Show and interpret the results.
e. Test the hypothesis against the alternative that it is positive at a 1% level of significance. What is your conclusion?
f. In the regression equation, create a residual plot and a residual histogram. Import the two graphs into your Word document.
2. Open file beer.wfl into EViews. Here is the description of the data:
a. Estimate a log-log model. Copy the equation with the estimated coefficients into your Word document.
b. Interpret the estimated coefficients of PB and Income.
c. From your estimation output, discuss the statistical significance of each coefficient. Could you reject the null hypothesis that each coefficient if equal to zero against the alternative that it is different from zero at 5% level of significance? Explain.
d. What can you conclude about the overall significance of the model? (Discuss the result of the F-test).
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