Answer :
Final answer:
The 3-year moving average and weighted moving average use past data to forecast future sales, the latter assigning more weight to more recent data. The Mean Squared Error (MSE) measures the average of the squares of the errors—that is, the average squared difference between the estimated values and the actual value.
Explanation:
The 3-year moving average forecasts are calculated by adding the number of sales from three consecutive years and dividing by three. For example, the forecast for year 4 would be the average of the sales from years 1, 2, and 3. This process is repeated for the subsequent years. The weighted moving average follows a similar concept, but assigns more importance, or weight, to certain instances. In this case, more recent years are given more weight. So, for the weighted average forecast for year 4, the sales for year 3 are multiplied by 2, while the sales for years 1 and 2 are multiplied by 1. These products are added together and then divided by the sum of the weights. Lastly, the MSE, or Mean Squared Error, is found by subtracting the actual sales values from the forecasted values, squaring these differences, summing them all up, and then dividing by the number of forecasts made.
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