Question

“Time series decomposition involves thinking of a series as a combination of level, trend, seasonality and noise components.” Define any two of these components.

Hint:

Tip: Trend = long-term direction; Seasonality = repeated short-term cycles.

Answer 1

Time series decomposition separates intricate time-dependent data into fundamental, understandable segments.
Key components include:
1. Trend — This component illustrates the data's long-term trajectory over time, indicating whether values are generally rising, falling, or stable. For example, consistent annual sales growth signifies an upward trend.
2. Seasonality — This component identifies recurring patterns or cycles at fixed intervals, such as monthly, quarterly, or annual effects. An example is increased ice cream sales during summer months.
Additional components are Level (the average value) and Noise (random fluctuations).
Collectively, these elements aid in predicting future values and comprehending temporal patterns.