I’m following this tutorial : https://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/
I have a simple question on the part about Stationarity.
There are 3 cases. For each case, there is a plot of mean and std variation, and a Dickey-Fuller test.
But it’s not logical :
Why the 2nd case is the best one (1% critical value) while the plot shows a bigger variation on mean and std variation than the 1st case (5% critical value) and the 3th case (10% critical value)
By the way, the 3th case is clearly the best one according to the plot as the mean and std are clearly more constant than in others plot, but the Dickey-Fuller test says the opposite.
Do you have any explanations ?