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Time series data refers to a sequence of observations arranged in chronological order, such as annual GDP figures and population statistics. The primary objective of time series modeling is data forecasting, including applications like predicting future sales volumes and stock price movements. This involves key techniques like trend decomposition, seasonal adjustment, and stationarity transformation.

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