Question

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 eight weeks follow. Weekly Gross Revenue ($1,000s) Television Advertising ($1,000s) Newspaper Advertising ($1,000s) 1.5 4.2 2.5 a. Develop an estimated regression equation with the amount of television advertising as the independent variable (to 1 decimal). Revenue = + TVAdv b. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables (to 2 decimals). Revenue = + TV Adv + NVAdv c. Is the estimated regression equation coefficient for television advertising expenditures the same in part (a) and in part (b)? - Select your answer - d. Predict weekly gross revenue for a week when $3.2 thousand is spent on television advertising and $2 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

Answer 1

a)

Regression Statistics
Multiple R	0.6193
R Square	0.3836
Adjusted R Square	0.2808
Standard Error	2.5817
Observations	8
ANOVA
	df	SS	MS	F	Significance F
Regression	1	24.9	24.9	3.73	0.1015
Residual	6	40.0	6.7
Total	7	64.9
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	88.6232	3.3618	26.3619	0.0000	80.3972	96.8492
X	1.9614	1.0151	1.9323	0.0508	-0.5224	4.4451

Revenue = 88.6 + 2.0*Tv Ads

b)

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.731044
R Square	0.534425
Adjusted R Square	0.348195
Standard Error	2.457811
Observations	8
ANOVA
	df	SS	MS	F	Significance F
Regression	2	34.67081	17.33541	2.869702904	0.147902
Residual	5	30.20419	6.040837
Total	7	64.875
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	82.13378	6.019841	13.64385	3.79265E-05	66.65929	97.60827	66.65929	97.60827
Tv Ads	2.784973	1.163007	2.394632	0.062031172	-0.20463	5.774577	-0.20463	5.774577
NV Ads	1.561259	1.226641	1.272792	0.259062047	-1.59192	4.714441	-1.59192	4.714441

revenue = 82.13 + 2.78*TV ads + 1.56*NV ads

c)

NO

d)

revenue = 82.13 + 2.78*3.2 + 1.56*2 = $ 94.15 in thousands