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The two main goals of time series analysis are to understand and model the underlying patterns in historical data, such as trends, seasonality, and cyclic behavior, and to make forecasts about future values based on these patterns. By analyzing time-dependent data, analysts aim to identify relationships and dependencies that can inform decision-making and improve predictive accuracy.

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