A time series contains a sequence of data points observed at specific intervals over time. A time series prediction uses a model to predict future values based on previously observed values. The natural temporal order of time series data makes analysis of time series different from cross-sectional or spatial data analyses, neither of which depends on a time component.
Time series predictions can be useful in a variety of settings, from processing signal data streaming from a sensor at an industrial site to monitoring trends in a financial market or maintaining inventory in a commercial setting. In all these scenarios, recent data can be used to inform predictions about future goal values.
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