Time Series Analysis Seasonal Decomposition 1

Question 1

What are the four classical components of a time series decomposition?

Accepted Answer

Trend, Seasonality, Cyclical, and Irregular (Residual)

Answer

Classical decomposition separates a series into trend, seasonal, cyclical, and irregular (noise) components.

Question 2

In additive decomposition, how are the components combined?

Accepted Answer

Y = Trend + Seasonal + Residual

Answer

Additive decomposition assumes the components sum together, appropriate when seasonal fluctuations are roughly constant in magnitude.

Question 3

When should multiplicative decomposition be preferred over additive?

Accepted Answer

When seasonal variation grows proportionally with the trend level

Answer

Multiplicative decomposition suits series where seasonal swings increase as the series level increases, reflecting proportional variation.

Question 4

What is STL decomposition?

Accepted Answer

Seasonal and Trend decomposition using Loess

Answer

STL uses locally weighted regression (Loess) to flexibly extract trend and seasonal components, handling complex and changing seasonality.

Question 5

What does the seasonal index represent in classical decomposition?

Accepted Answer

The average deviation from the trend for each period within a season

Answer

A seasonal index captures how much a given seasonal period (e.g., month) typically deviates from the overall trend level.

Time Series Analysis Practice Test