a.With your Excel Worksheet (printout):

i.Write an estimated log-linear demand function. In(Quantity=B+In(Price)+In(Income); InQuantity=1.29-.07InPrice-.03InIncome

ii.Evaluate the overall statistical significance of the estimated demand function. The estimated demand function shows that if the price or income increases by 1% then the quantity demanded will decrease by .07%. With the high value of adjusted R square this is the best fitted regression model.

iii.Evaluate the statistical significance of each independent economic variable on quantity demanded of alkaline batteries.

b.Derive the nonlinear (multiplicative) form of your estimated log-linear demand function in (a). Clearly show your steps.

c.Estimate income elasticity of demand for alkaline batteries. Clearly show your steps and calculations.

d.Determine the quantity of batteries demanded at the unit price of $2.65 and average consumers' income of $80.92. Clearly show your steps and manual (hand and calculator) calculations in 4 decimal points.

SUMMARY OUTPUT Regression Statistics Multiple R 0.970326077 R Square 0.941532695 Adjusted R Square 0.938990639 Standard Error 0.003077832 Observations 49 ANOVA df SS MS F Significance F Regression 2 0.007017301 0.00350865 370.3822533 4.35513E-29 Residual 46 0.00043576 9.47305E-06 Total 48 0.007453061 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 99.0% Upper 99.0% Intercept 1.29026453 0.413388205 3.121193379 0.003109379 0.45815723 2.122371829 0.179484844 2.401044215 In Price -0.07209184 0.002708234 -26.61950286 1.37165E-29 -0.077543232 -0.066640448 -0.079368901 -0.064814779 In Income -0.03131366 0.094207924 -0.33238881 0.741105666 -0.220944374 0.158317055 -0.284451621 0.221824302