Decomposition of time series

Decomposition of time series is a statistical technique used to analyze and understand the underlying components of a time series dataset. The main goal of this process is to separate the time series into its constituent parts so that each component can be studied and understood independently. Time series data typically exhibits four main components: 1. **Trend**: This component represents the long-term movement or direction in the data. It indicates whether the data values are increasing, decreasing, or remaining constant over time.