What is Autoregression? | Autoregression explained

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Autoregression is a powerful tool for predicting future values based on past data points in a time series. A time series consists of observations collected over time, which can be recorded at regular or irregular intervals.
By examining the relationship between past and present values, autoregression models can capture trends, patterns, and other hidden factors that influence future data points. These models work by using previous observations to predict the next value in the series, essentially forecasting what might happen next.
This makes autoregression especially useful in areas like stock prices, weather patterns, and sales forecasting, where trends over time are crucial for making accurate predictions.
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