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 breaks down complex time-based data into simpler, interpretable parts.
Two key components are:
1. Trend — The trend component shows the long-term direction in the data over time.
It highlights whether values are generally increasing, decreasing, or remaining stable.
For example, a steady rise in yearly sales indicates an upward trend.
2. Seasonality — This component captures repeating patterns or cycles at regular intervals.
Seasonal effects can be monthly, quarterly, or annual.
For instance, higher ice cream sales during summer months show seasonality.
Other components include Level (average value) and Noise (random variations).
Together, these help in forecasting and understanding time-based patterns.