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7-TimeSeries/2-ARIMA/README.md
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@ -14,7 +14,7 @@ In this lesson, you will discover a specific way to build models with [ARIMA: *A
## General concepts ## General concepts
To be able to work with ARIMA, there's some concepts you need to know about: To be able to work with ARIMA, there are some concepts you need to know about:
- 🎓 **Stationarity**. From a statistical context, stationarity refers to data whose distribution does not change when shifted in time. Non-stationary data, then, shows fluctuations due to trends that must be transformed to be analyzed. Seasonality, for example, can introduce fluctuations in data and can be eliminated by a process of 'seasonal-differencing'. - 🎓 **Stationarity**. From a statistical context, stationarity refers to data whose distribution does not change when shifted in time. Non-stationary data, then, shows fluctuations due to trends that must be transformed to be analyzed. Seasonality, for example, can introduce fluctuations in data and can be eliminated by a process of 'seasonal-differencing'.

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