Collaborative Data Science
Autocorrelation plots are graphical representations that show the correlation of a time series with its own past values over various lags. These plots help identify patterns, trends, and seasonality in time series data, making them essential for understanding the temporal dependencies that exist within the data. By visually assessing autocorrelations, analysts can determine if a time series is stationary or if it exhibits cyclical behaviors that might affect forecasting models.
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