Detecting and correcting for unit roots
Let’s talk about unit roots first since this is what is most commonly tested for stationarity. Time series analysis has its roots in econometrics and statistics and unit root is a concept derived directly from those fields.
Unit roots
Unit roots are quite complicated to understand fully but to develop some intuition, we can look at a simplification. Let’s consider an autoregressive model of order 1(AR(1) model):
If we think about the different values of 
in the equation, we can come up with three scenarios (Figure 7.2):
: When 
is greater than 1, every successive value in the time series is multiplied by a number greater than 1, which means it will have a strong and rapidly increasing/decreasing trend and thereby be non-stationary.
: When is less than 1, every successive value in the time series is multiplied by a number less than 1, which means over the long term, the mean of the series trends to zero...
