Question

eBook Video Use computer software packages, such as Minitab or Excel, to solve this problem. The owner of Showtime Movie Theaters, Inc, would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of elght weeks follow. Weekly Television Newspaper Gross Revenue Advertising Advertising ($1,000s) ($1,000s) ($1,000s) 101 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 96 3.0 3.3 94 3.5 2.3 94 2.5 4.2 103 30 2.5 a. Develop an estimated regression equation with the amount of television advertising as the independent variable (to 1 decimal), Reverue TVAdv b. Develop an estimated regression equation with both television advertising newspaper advertising as the independent variables (to 2 decimals) Rever ue TVAdv+ NVAdv c. Is the estimated regression equation coefficent for television advertising expenditures the same in part (a) and in part (b)? Select your answer d. Predict weekdy gross revenue for a week when $3.3 thousand is spent on television advertising and $1.6 thousand is spent on newspaper advertising NOTE: To compute the predicted revenues, use the coefficients you have computed rounded to two decimals, as you have entered them here. Then, also round your predicted revenue to two decimal places in thousands Oloon Aevy

Answer 1

(a)

Using Excel Data analysis Toolpak we get :

SUMMARY OUTPUT Regression Statistics Multiple R 0.60 R Square 0.36 Adjusted R Square 0.25 Standard Error 3.79 Observations 8 ANOVA Significance F df SS MS F 3.32 Regression 1 47.68 47.68 0.12 Residual 6 86.19 14.37 Total 7 133.88 Coefficients Standard Error P-value t Stat Lower 95% Upper 95% Intercept 87.0 4.9 17.6 0.0 74.9 99.0 Television Advertising 2.7 1.5 1.8 0.1 -0.9 6.4

So, Estimated regression equation is :

Revenue 87.02.7 TV Adv

(b)

SUMMARY OUTPUT Regression Statistics Multiple R R Square 0.637 0.406 Adjusted R Square 0.169 Standard Error 3.987 Observations ANOVA Significance F df SS MS F Regression 2 54.39 27.20 1,71 0.27 Residual 79.48 15.90 Total 7 133.88 t Stat Coefficients Standard Error P-value Lower 95% Upper 95% Intercept Television Advertising 9.765 56.495 81,60 8.356 0.000 106.701 3,40 1.887 1.801 0.132 -1.453 8.247 Newspaper Advertising 0.650 1.29 1.990 0.545 -3.822 6.408

So, Estimated regression equation is :

Revenue 81.603.40 TV Adv1.29 NV Adv

c)

The estimated regression equation coefficient for television advertising expenditure is not same for part(a) and part(b).

d)

Revenue 81.60 3.40 3.3 1.291.6 $94.88