Alfonso Solution

A. Determine the impact of Alfonso’s advertising on Alfonso’s sales

Model Summary |

Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |

1 | .010a | .000 | -.042 | 222476.423 |

a. Predictors: (Constant), alfo_advert |

ANOVAa |

Model | Sum of Squares | df | Mean Square | F | Sig. |

1 | Regression | 116827000.694 | 1 | 116827000.694 | .002 | .962b |

| Residual | 1187898209095.345 | 24 | 49495758712.306 | | |

| Total | 1188015036096.038 | 25 | | | |

a. Dependent Variable: alfo_sales |

b. Predictors: (Constant), alfo_advert |

Coefficientsa |

Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. |

| B | Std. Error | Beta | | |

1 | (Constant) | 2152805.912 | 68986.206 | | 31.206 | .000 |

| alfo_advert | -.170 | 3.494 | -.010 | -.049 | .962 |

a. Dependent Variable: alfo_sales |

alfo_sales = 2152805.912 – 0.170 alfo_advert.

According to the model we can conclude that:

* The alfonso’s advertising doesn’t have significan influence to alfonso’s sales (because R2 < 0.05)

* The model doesn’t respect the economy theory advertising should has the positif influence to sales, in this model we can see that advertising has the negative influence

* Then, we can conclude that if we just have the information from alfonso’s sales and alfonso’s advertising, the alfonso’s should consider to stop or not advertise because the result from the advertising is not significant.

B. Plot Alfonso’s sales and total market sales over time, then calculate the correlation between the gap of alfonso sales and total market with the gap of advertising.

From the chart we can see that the alfonso’s sales and total sales have the similar pattern.

Correlations |

| sales_gap | advert_gap |

sales_gap | Pearson Correlation | 1 | -.573** |

| Sig. (2-tailed) | | .002 |

| N | 26 | 26 |

advert_gap | Pearson Correlation | -.573** | 1 |

| Sig. (2-tailed) | .002 | |

| N | 26 |...