A stationary forecasting model is appropriate for a time series which exhibits primarily:
A)trend.
B)cyclical influences.
C)seasonal components.
D)random variation.

Question

Quizplus · Accepted Answer

A stationary forecasting model is appropriate for time series with random variation because the mean, variance, and autocorrelation structure of the series do not change over time. If the series exhibits trend, cyclical influences, or seasonal components, it is not stationary and requires modeling techniques that account for those factors.

A Stationary Forecasting Model Is Appropriate for a Time Series