Additive seasonal variation in time series data means a forecast can only be found by multiplying the trend times the seasonal factor (or index).

Question

Quizplus · Accepted Answer

Additive seasonal variation means that the seasonal component is added to the trend in order to obtain a forecast, while multiplicative seasonal variation means that the seasonal component is multiplied by the trend to obtain a forecast. Therefore, a forecast in the case of additive seasonal variation would be found by adding the trend and seasonal factor/index.

Additive Seasonal Variation in Time Series Data Means a Forecast