Autocorrelation, also known as serial correlation, is a statistical measure that assesses the correlation of a signal with a delayed copy of itself as a function of the delay (or time lag). It essentially quantifies how similar a time series is with a lagged version of itself over different time periods. In the context of time series data, autocorrelation can help identify patterns over time, such as seasonality or cyclic behaviors.
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