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Adf stationarity test python

Adf stationarity test python
  1. How do you check data stationary?
  2. What does the ADF test show?
  3. How to interpret ADF test results?

How do you check data stationary?

Two tests for checking the stationarity of a time series are used, namely the ADF test and the KPSS test. Detrending is carried out by using differencing technique and the same will be covered in future articles on Statistical tests to check stationarity in Time Series.

What does the ADF test show?

In statistics, an augmented Dickey–Fuller test (ADF) tests the null hypothesis that a unit root is present in a time series sample. The alternative hypothesis is different depending on which version of the test is used, but is usually stationarity or trend-stationarity.

How to interpret ADF test results?

ADF (Augmented Dickey-Fuller) test is a statistical significance test which means the test will give results in hypothesis tests with null and alternative hypotheses. As a result, we will have a p-value from which we will need to make inferences about the time series, whether it is stationary or not.

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