A weighted moving average method that calculates the average of a time series by giving recent demands more weight than earlier methods is called
A) seasonally adjusted smoothing.
B) exponential smoothing.
C) multiplicative seasonal method.
D) cumulative tracking error.

Question

Quizplus · Accepted Answer

The method described is an example of exponential smoothing, where recent demands are given more weight than earlier demands by incorporating a smoothing parameter that dampens the influence of past demands on the average. Seasonally adjusted smoothing and multiplicative seasonal methods refer to techniques specifically designed to handle seasonal patterns in the data, while cumulative tracking error is not a method at all but a performance measure used to evaluate forecasting accuracy.

A Weighted Moving Average Method That Calculates the Average of a Time