Question

In the Exponential Smoothing method of forecasting, the choice

of the best smoothing factor is one which is associated where the
mean-squared-error is:
a) large
b) random
c) maximum
d) minimum

Answer 1

In Exponential Smoothing, the optimal smoothing factor is associated with the minimum mean-squared-error (MSE). Selecting this factor is crucial for minimizing the forecast error and improving accuracy. The correct option is (d) minimum.

Step-by-step explanation:

In the Exponential Smoothing method of forecasting, the selection of the smoothing factor (α) is critical for producing accurate forecasts. The smoothing factor is chosen to minimize the difference between the forecasted values and the actual values. This difference is often measured by the mean-squared-error (MSE), which is the average of the squared differences between the forecasted values and the actual observations.

To determine the best smoothing factor, we evaluate multiple factors and compute the MSE for each. The objective is to select the smoothing factor that results in the minimum MSE. A lower MSE indicates that the forecast is more accurate and closely matches the real data. Selecting a factor associated with a large, random, or maximum MSE would lead to less accurate forecasts and is not desirable in practice.

Hence, in the context of the Exponential Smoothing method, the optimal choice of the smoothing factor is associated with a minimum mean-squared-error. Therefore, the correct option for this question is (d) minimum.