Time Series Analysis, Lecture 16: Seasonal ARIMA Models

We introduce seasonality (periodic fluctuations) into our ARIMA model. This type of model is very useful in practice as time series datasets often exhibit seasonality, e.g. every seven days, every 12 months, etc. We also look at what happens to the autocorrelation function for seasonal time series data.

[tochoXK]

Too much theoretical stuff, too much complex notation.
I'd prefer a straightforward explanation how SARIMA works (like "here are all the relevant formulas, here's an example-based explanation of the formulas).