# Vodka Harvard Case Solution & Analysis

When include price per unit:

 Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1 .812a .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)

 ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 5.660E8 5 1.132E8 120.039 .000a 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)

 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1278.068 86.027 14.857 .000 Print -.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 Statisticsa 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 Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1 .787a .619 .613 1026.535 .465 a. Predictors: (Constant), gdp, print, broad, news, outdoor b. Dependent Variable: sales

Figure 13: model summary (GDP included)

 ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 5.333E8 5 1.067E8 101.226 .000a 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 Statisticsa 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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