Question

еВook 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 eight weeks follow. Weekly Television Newspaper Gross Revenue Advertising Advertising ($1,000s) ($1,000s) ($1,000s) 104 5.0 1.5 90 2.0 2.0 95 4.0 1.5 2.5 92 2.5 102 3.0 3.3 94 3.5 2.3 94 2,5 4.2 98 3.0 2,5 a. Develop an estimated regression equation with the amount of television advertising as the independent variable (to 1 decimal) Revenue TVAdy b. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables (to 2 decimals) TVAdv Revenue NVAdv c. Is the estimated regression equation coefficient for television advertising expenditures the same in part (a) and in part (b)? No, the coefficients are not the same ] d. Predict weekly gross revenue for a week when $3.6 thousand is spent on television advertising and S1.7 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

Ans a )  using excel >stat>basic stat>regression

		SUMMARY OUTPUT
		Regression Statistics
	Multiple R	0.69853
	R Square	0.487945
	Adjusted R Square	0.402602
	Standard Error	3.751114
	Observations	8
	ANOVA
		df	SS	MS	F	Significance F
	Regression	1	80.44988	80.44988	5.717484	0.053943
	Residual	6	84.42512	14.07085
	Total	7	164.875
		Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
	Intercept	84.88406	4.884596	17.37791	2.33E-06	72.93188	96.83623
	tv add	3.52657	1.474857	2.391126	0.053943	-0.08228	7.135416

Revenue = 84.9 + 3.5 TV add

b )

		SUMMARY OUTPUT
		Regression Statistics
	Multiple R	0.796743
	R Square	0.634799
	Adjusted R Square	0.488718
	Standard Error	3.470232
	Observations	8
	ANOVA
		df	SS	MS	F	Significance F
	Regression	2	104.6624	52.33122	4.34554	0.080599
	Residual	5	60.21256	12.04251
	Total	7	164.875
		Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
	Intercept	74.67656	8.499531	8.785962	0.000317	52.82782	96.5253
	tv add	4.822083	1.642072	2.936584	0.032385	0.601002	9.043163
	news add	2.455779	1.731919	1.417953	0.215405	-1.99626	6.907818

Revenue = 74.7+ 4.8 TV add + 2.5 News Add

ans 3 ) No, the coefficient for television advertising expenditure is not same.

Ans 4) For tv add = $ 3.6 , News Add = 1.7

predicted Revenue = 74.7+ 4.8 *3.6 + 2.5*1.7 = 96.23