When include price per unit:
Model Summary^{b} 

Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
DurbinWatson 
1 
.812^{a} 
.660 
.655 
971.078 
.522 
a. Predictors: (Constant), price per unit, broad, news, print, outdoor
b. Dependent Variable: sales

Figure 9: model summary (price per unit included)
ANOVA^{b} 

Model 
Sum of Squares 
df 
Mean Square 
F 
Sig. 

1  Regression 
5.660E8 
5 
1.132E8 
120.039 
.000^{a} 
Residual 
2.914E8 
309 
942993.306 



Total 
8.574E8 
314 




a. Predictors: (Constant), price per unit, broad, news, print, outdoor
b. Dependent Variable: sales 
Figure 10: Anova (price per unit included)
Coefficients^{a} 

Model 
Unstandardized Coefficients 
Standardized Coefficients 
t 
Sig. 

B 
Std. Error 
Beta 

1  (Constant) 
1278.068 
86.027 

14.857 
.000 
.023 
.120 
.007 
.194 
.846 

News 
.639 
.135 
.193 
4.727 
.000 

Broad 
.658 
.039 
.585 
16.780 
.000 

Outdoor 
.099 
.011 
.385 
8.707 
.000 

Priceperunit 
7.114 
1.061 
.262 
6.703 
.000 

a. Dependent Variable: sales 
Figure 11: Coefficients (price per unit included)
Residuals Statistics^{a} 


Minimum 
Maximum 
Mean 
Std. Deviation 
N 
Predicted Value 
500.13 
10414.89 
1429.32 
1342.567 
315 
Residual 
6379.618 
3830.601 
.000 
963.316 
315 
Std. Predicted Value 
1.437 
6.693 
.000 
1.000 
315 
Std. Residual 
6.570 
3.945 
.000 
.992 
315 
a. Dependent Variable: sales 
Figure 12: residuals (price per unit included)
Advertising model mentioned above does change if other variables are added in it so as to analyze the impact of all advertising variables along with a price per unit on total sales of the vodka industry. When R square is added along with advertising variables as predictors to analyze whether adding price per unit impacts the total sales of the company or not. R square shown in the model summary is 0.660, which shows that 66% of the predictors impact total sales of the company. It interprets that in case any of the advertising media along with a price per unit has changed then it will change the total sales by 66% as well.
Annova table in the analysis has shown that the connection between dependent and independent variable is significant as well that shows price per unit of vodka does impact the total sales of the company.
Initially, four predictors were used in the model to see their impact on total sales of the company. Those four predictors were media, broad, news and outdoor. After that, price per unit in the model has been added as well in order to analyze the combined effect in the total sales of the company. By adding price per unit, the B is found to be negative for the price per unit but the significance level is 0.000 that indicates that greater price per unit will be; so lesser will be the sales.
The biggest change after adding a price per unit in the model is a change in the significance level of print advertising that is 0.846.
When include GDP:
Model Summary^{b} 

Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
DurbinWatson 
1 
.787^{a} 
.619 
.613 
1026.535 
.465 
a. Predictors: (Constant), gdp, print, broad, news, outdoor
b. Dependent Variable: sales

Figure 13: model summary (GDP included)
ANOVA^{b} 

Model 
Sum of Squares 
df 
Mean Square 
F 
Sig. 

1  Regression 
5.333E8 
5 
1.067E8 
101.226 
.000^{a} 
Residual 
3.277E8 
311 
1053774.957 



Total 
8.611E8 
316 




a. Predictors: (Constant), gdp, print, broad, news, outdoor
b. Dependent Variable: sales

Figure 14: Anova (GDP included)
Residuals Statistics^{a} 


Minimum 
Maximum 
Mean 
Std. Deviation 
N 
Predicted Value 
617.37 
10147.93 
1420.71 
1299.159 
317 
Residual 
6008.257 
4086.284 
.000 
1018.382 
317 
Std. Predicted Value 
.618 
6.718 
.000 
1.000 
317 
Std. Residual 
5.853 
3.981 
.000 
.992 
317 
a. Dependent Variable: sales

Figure 15: Residuals (GDP included)
The same model has been used here as well; however, one variable has been added in the test as well to see the impact of it on total sales and that variable is GDP. After adding total sales in the model, R square has increased to 0.619 that is 61.9%. Model that was first used with the variables that include: news, print, broad and outdoor have R square equals to 61.1%, which shows that the value of R square has increased to 61.9% that is very minimal; thus, it is concluded that adding GDP does not have a significant impact on total sales in the vodka industry..............................
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