Time evolving phenomena are fundamental to many disciplines. Understanding what happened and foreseeing how different variables will evolve is key knowledge for making correct, informed decisions.
Time series analysis is a broad field, with many different methods to detect patterns, predict behaviors, and decompose the time evolution into known and previously studied shapes. We are going to discuss some of them, focusing on the ones that are easily solved using Excel. The idea, as usual, is that our machines learn about the details in the data and can extract useful knowledge about the past and the possible future developments.
In this chapter, we will cover the following topics:
- Modeling and visualizing time series
- Forecasting time series automatically in Excel
- Studying the stationarity of a time series
