= Data differencing
{wiki=Data_differencing}
Data differencing is a technique used primarily in time series analysis to remove trends and seasonality from data, making it stationary. A stationary time series is one whose statistical properties such as mean, variance, and autocorrelation are constant over time, which is a crucial requirement for many time series modeling techniques, including ARIMA (AutoRegressive Integrated Moving Average). \#\#\# How Data Differencing Works The basic idea behind differencing is to compute the difference between consecutive observations in the time series.
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