This article will walk through the steps in Time Series Analysis 1 - Identifying Structure and use this knowledge to forecast. Here we will tackle the seasonality component as well.
In this article we tackle a generated set of progressively more complex time series datasets. From a random series to an ARIMA series with seasonality as well as a series with a structural change. For each of these time series we apply the traditional techniques used in time series analysis to ascertain the underlying structure. In a follow up article we will make the final step to use what we've learned to forecast into the future.