Question

In: Statistics and Probability

1. The owner of Showtime Movie Theaters, Inc. would like to estimate weekly gross revenue as...

1. The owner of Showtime Movie Theaters, Inc. would like to estimate weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow.

Weekly Gross

Television

Newspaper

Radio

Revenue

Advertising

Advertising

Advertising

($1000s)

($1000s)

($1000s)

($1000s)

96

5

1.5

0.3

90

2

2

0.2

95

4

1.5

0.3

92

2.5

2.5

0.1

95

3

3.3

0.4

94

3.5

2.3

0.4

94

2.5

4.2

0.3

94

3

2.5

0.3

  1. Develop an estimated regression equation in Excel with the amount of television advertising as the independent variable
  2. Develop an estimated regression equation in Excel with both television advertising and newspaper advertising as the independent variables
  3. Develop an estimated regression equation in Excel with all three independent variables: television advertising, newspaper advertising, and radio advertising
  4. Is the estimated regression equation coefficient for television advertising expenditures the same in par a), in part b) and in part c)? Interpret the coefficient in each case
  5. Obtain and compare the multiple coefficient of determination and the adjusted multiple coefficient of determination for parts a), b) and c). How does the coefficient of determination changes as a result of adding more independent variables in the equation?
  6. What is the estimate of the weekly gross revenue for a week when $3500 is spent on television advertising, $1800 is spent on newspaper advertising, and $350 in radio advertising?

I ONLY need help with D through F. Please show how to do in Excel. Thank you!!

Solutions

Expert Solution

Ans a )

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.807807
R Square 0.652553
Adjusted R Square 0.594645
Standard Error 1.215175
Observations 8
ANOVA
df SS MS F Significance F
Regression 1 16.6401 16.6401 11.26881 0.015288
Residual 6 8.859903 1.476651
Total 7 25.5
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 88.63768 1.582367 56.01588 2.17E-09 84.76577 92.50959
Tv Ads 1.603865 0.477781 3.356905 0.015288 0.434777 2.772952

Ans b )

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.958663
R Square 0.919036
Adjusted R Square 0.88665
Standard Error 0.642587
Observations 8
ANOVA
df SS MS F Significance F
Regression 2 23.43541 11.7177 28.37777 0.001865
Residual 5 2.064592 0.412918
Total 7 25.5
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 83.23009 1.573869 52.88248 4.57E-08 79.18433 87.27585
Tv Ads 2.290184 0.304065 7.531899 0.000653 1.508561 3.071806
News ads 1.300989 0.320702 4.056697 0.009761 0.476599 2.125379

Ans c )

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.965593
R Square 0.93237
Adjusted R Square 0.881648
Standard Error 0.656613
Observations 8
ANOVA
df SS MS F Significance F
Regression 3 23.77544 7.925146 18.38183 0.00838
Residual 4 1.724561 0.43114
Total 7 25.5
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 83.5228 1.641648 50.87741 8.93E-07 78.96485 88.08074
Tv Ads 2.079043 0.39123 5.314125 0.006029 0.992815 3.165271
News ads 1.124548 0.383224 2.934439 0.042625 0.060547 2.18855
Radio ad 2.84172 3.199861 0.888076 0.424677 -6.04252 11.72596

Ans d ) the estimated regression equation coefficient for television advertising expenditures is not same in par a), in part b) and in part c)

in a ) for every one $ increase in tv ad there is 1.60$ increase in revenue

in b ) for every one $ increase in tv ad there is 2.29$ increase in revenue

in c ) for every one $ increase in tv ad there is 2.07$ increase in revenue

Ans e) for a )

R Square 0.652553
Adjusted R Square 0.594645

for b

R Square 0.919036
Adjusted R Square 0.88665

for c

R Square 0.93237
Adjusted R Square 0.881648

the coefficient of determination increases as we add more independent variables in the equation.

ANs e ) revenue = 83.5228+ 2.079 Tv ads + 1.125 news ad + 2.842 radio ad

revenue= 83.5228+ 2.079*3500+1.125*1800+2.842*350 = 10378.96


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