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Auto correlation is a characteristic of data which shows the degree of similarity between the values of the same variables over successive time intervals. When you have a series of numbers, and there is a pattern such that values in the series can be predicted based on preceding values in the series, the series of numbers is said to exhibit autocorrelation. This is also known as serial correlation and serial dependence. The existence of autocorrelation in the residuals of a model is a sign that the model may be unsound . Autocorrelation is diagnosed using a correlogram (ACF plot) and can be tested using the Durbin-Watson test.
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