Autocorrelation is a statistical concept that measures the relationship between a time series and a lagged version of itself over successive time intervals. In simpler terms, it assesses how a data set correlates with itself at different points in time. When analyzing a time series, autocorrelation helps to identify patterns, trends, or seasonal variations by determining whether past values influence future values.
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