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 2.0 2.0 2.5 3.0 a. Develop an estimated regression equation with the amount of television advertising as the independent variable (to 1 decimal) Revenge = + TV Adv b. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables (to 2 decimas) Revenue = TV Adv + NV Ady C. Is the estimated regression equation coefficient for television advertising expenditures the same in part (a) and in part (b) d. Predict weekly gross revenue for a week when $3.5 thousand is spent on television advertising and 31.6 thousand is spent on newspaper advertising NOTE: To compute the predicted revenues, use the coeficients 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	0.7666
R Square	0.5877
Adjusted R Square	0.5190
Standard Error	3.3863
Observations	8
ANOVA
	df	SS	MS	F	Significance F
Regression	1	98.1	98.1	8.55	0.0265
Residual	6	68.8	11.5
Total	7	166.9
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	83.4638	4.4095	18.9280	0.0000	72.6740	94.2535
X	3.8937	1.3314	2.9245	0.0132	0.6359	7.1516

Revenue = 83.46 + 3.89*TV ads

b)

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.793119
R Square	0.629037
Adjusted R Square	0.480652
Standard Error	3.518648
Observations	8
ANOVA
	df	SS	MS	F	Significance F
Regression	2	104.9706	52.48529	4.23922	0.083816
Residual	5	61.90442	12.38088
Total	7	166.875
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	78.01567	8.618115	9.052521	0.000275	55.8621	100.1692	55.8621	100.1692
x1	4.58518	1.664982	2.753892	0.040124	0.305208	8.865152	0.305208	8.865152
x2	1.310736	1.756082	0.746398	0.489013	-3.20342	5.824888	-3.20342	5.824888

revenue = 78.02 + 4.59*TV ads + 1.31*NV ads

c) NO

d)

revenue = 78.02 + 4.59*TV ads + 1.31*NV ads

revenue = 78.02 + 4.59*3.5 + 1.31*1.6 = 96.18