The decomposition of time series data down to its components is one of the core methods in time series analysis. The use of this method is part of descriptive analysis, as it can provide some useful insights into series patterns and structures. Those insights can be utilized to identify the best approaches and models to be used with a series.
The focus of this chapter has been on the classical seasonal decomposition process with MA, one of the most common decomposition methods. Although this method is not the most advanced or accurate, it is the basis of most advanced methods. Therefore, understanding the mechanisms of this process, such as the role of the MA, means that you can apply more sophisticated methods with minimum effort.
In the next chapter, we will focus on the analysis of the seasonal component of time series data.
