Summary
In this chapter, we became familiar with time series and learned how to process and generate them. We also found out how time series processes are analyzed and what the main model types of these processes are. After knowing the models, we learned how to identify the most appropriate model for a time series, and having determined the model, we could get the forecast data and confidence intervals for future data sets. Using Mathematica functions, we were able to check observation data for stationarity, autocorrelation, and invertibility.
In the next chapter, we will move on to the verification of various statistical hypotheses on the types of sample parameters.