Statistical Methods for Data Science
Autocorrelation is a statistical measure that evaluates the correlation of a time series with its own past values. It helps identify patterns in data over time, making it essential for understanding how current values are related to their historical counterparts. A strong autocorrelation suggests that past observations significantly influence future values, which is crucial for effective forecasting and model evaluation.
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