Which term describes random noise in time series data?

Which term describes random noise in time series data?

• A. Seasonal variation
• B. Secular variation
• C. Cyclical variation
• D. Irregular variation

Answer: (D)

In time series analysis, the unpredictable, non-repeating fluctuations left after removing the systematic parts are described as irregular variation. This component captures random noise or measurement error that doesn’t follow a fixed pattern or period. Seasonal variation is the regular, repeating pattern within a year or other cycle; secular variation is the long-run trend; cyclical variation consists of longer, irregular up-and-down movements tied to economic or other cycles. Because random noise has no stable pattern or timing, irregular variation best describes it.

In time series analysis, the unpredictable, non-repeating fluctuations left after removing the systematic parts are described as irregular variation. This component captures random noise or measurement error that doesn’t follow a fixed pattern or period. Seasonal variation is the regular, repeating pattern within a year or other cycle; secular variation is the long-run trend; cyclical variation consists of longer, irregular up-and-down movements tied to economic or other cycles. Because random noise has no stable pattern or timing, irregular variation best describes it.