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  3. ARIMA Models in Python

Exercise

Diagnostic summary statistics

It is important to know when you need to go back to the drawing board in model design. In this exercise you will use the residual test statistics in the results summary to decide whether a model is a good fit to a time series.

Here is a reminder of the tests in the model summary:

Test Null hypothesis P-value name
Ljung-Box There are no correlations in the residual
 Prob(Q)
Jarque-Bera The residuals are normally distributed Prob(JB)

An unknown time series df and the ARIMA model class are available for you in your environment.

Instructions 1/4

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  • Fit an ARMA(3,1) model to the time series df.
  • Print the model summary.