Time series decomposition

Time series decomposition is a better way of understanding the data in hand. Decomposing the model creates an abstract model that can be used for generalization of the data. Decomposition involves identifying trends and seasonal, cyclical, and irregular components of the data. Making sense of data with these components is the systematic type of modeling.

In the following section, we will look at these recurring properties and how they help analyze time series data.

Level

We have discussed moving averages with respect to time series before. The level can be defined as the average or mean of a bunch of time series data points.

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