Stationarity Check

The video tutorial explains how to use the ADFuller test from the statsmodels library to check the stationarity of a time series. It covers importing the necessary tools, preparing the data, executing the test, and interpreting the results. The tutorial concludes by confirming the stationarity of the series and suggests moving on to deep learning models.

What is the purpose of using the adfuller function in time series analysis?

How do you extract the ADF statistics from the result after performing the ADF test?

What are the critical values in the context of the ADF test, and how are they represented?

Explain the significance of the P value obtained from the ADF test results.

What conclusion can be drawn if the ADF value is greater than the critical values?