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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