This method, with no weights or smooth, outperformed. In a sense, this is not particularly surprising. While in the real world the tire business varies by season, in this example the demand numbers appear to have been randomized. Each of these methods is essentially the same, but for the weights of the months in question. However, since the demand function is not experiencing linear growth, none of these approaches can be expected to be particularly strong with respect to the forecast. Simple moving came closest to predicting the actual demand, so in this instance it was the most reliable. This forecast can be improved. Regardless of these figures, the business is seasonal. To improve the forecast, these different techniques can be applied to the last three instances of a given month. Thus, the trend over the past three months of January would be the best way to do this...