When would you use a Time series over a regression model

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Accepted Answer

Time series is used when data points are collected over time and have a sequential order, while regression is used for predicting continuous outcomes based on independent variables.

Time series is used when analyzing data points collected at regular intervals over time.
Regression models are used when predicting continuous outcomes based on independent variables.
Time series can capture trends, seasonality, and cyclic patterns in data, while regression may not be able to capture such dynamics.
Example: Using time series to forecast stock prices based on historical data, and using regression to predict customer churn based on demographic variables.

When would you use a Time series over a regression model

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