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Time series assumes that the data is ordered and dependent on time, while regression assumes that the data is independent and random. Time series uses methods such as smoothing, decomposition, autocorrelation, and ARIMA models, while regression uses methods such as linear, logistic, polynomial, and multivariate models.
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