Question

ries of sales data that provides with an R-value of (-0.66.) You manager wants you to 9) You have a se make a sales forecast for the next 6 months. Answer the following; this question is worth 9 points time series model, as discussed in class, would you be using when you see an R-value? odel a good tool to use to make a forecast given that you want at least 80% of the A) What B) Is this m response variable change attributable to the explanatory variable? Why2 C) What could you do to improve the use-ability of this tool?

Answer 1

R value = -0.66

R² = 0.4356.

This means that 43.56% of the variability in the sales can be explained by the variability in the explanatory variable. This number is on the lower side and doesnt really help to forecast well.

1. The following three techniques can be used for forecasting

1. Autoregression (AR)
2. Moving Average (MA)
3. Autoregressive Moving Average (ARMA)

2.

R² = 0.4356.

This means that 43.56% of the variability in the sales can be explained by the variability in the explanatory variable. This number is on the lower side and doesnt really help to forecast sales well.

Therefore, no the model is not good to forecast the sales.

3. We can increase the number of observations used in the model or we can increase the number of explanatory variables used in the model. In this way , we can better explain the variability in the sales & thus improve the R². This will in turn help us to improve the forecasting accuracy of sales.