Several statistical tests can be used to assess whether a dataset is stationary:
Augmented Dickey-Fuller Test (ADF): This test checks for a unit root in the data, with the null hypothesis being that the data is non-stationary. Kwiatkowski-Phillips-Schmidt-Shin Test (KPSS): This test has the null hypothesis that the data is stationary, and it is often used in conjunction with the ADF test for more robust conclusions. Phillips-Perron Test: Similar to the ADF test, it accounts for serial correlation in the error terms when testing for a unit root.
