# 10.2.3 Moving Average Forecast versus First-Order Exponential Smoothing Forecast

### Intended learning outcomes: Disclose formulas for the relationship between α and n. Present the relationship between α and n in tabular form. Present an example of linear regression.

The results of moving average and first-order exponential smoothing are comparable, to the extent that the mean age of the ob­served values corresponds mutually. Figure 10.2.3.1 shows the relationship between the number of observed values and the smoothing constant α.

Fig. 10.2.3.1       Formulas for the relationship between α and n.

Figure 10.2.3.2 shows the same relationship between α and n, using a tabular comparison of individual values.

Fig. 10.2.3.2       Relationship between α and n in tabular form.

Exercise: Comparing Moving Average Forecast versus First-Order Exponential Smoothing Forecast
This exercise demonstrates the different types of demand forecast.
The first graph calculates the forecast using first-order exponential smoothing while the second is calculated by a method of your choice. Get used to the effects of N (the number of considered periods in the past) as well as the smoothing constant α, by chosing different values for these variables.
The initial setting marks the 11th and 12th month of the current yeat as unknown (="-"). You may also change these parameters.