Autocorrelation Table Of Contents: What Is Autocorrelation? Assumption Of No Autocorrelation. Why No Autocorrelation Is Important? Common Causes Of Autocorrelation. Detecting Autocorrelation. Addressing Autocorrelation. Examples Of Autocorrelation In Residuals. (1) What Is Autocorrelation? In linear regression, autocorrelation refers to the correlation of the residuals (errors) of the model with themselves, particularly in time-series data or data with a sequential nature. The assumption of no autocorrelation is one of the key assumptions for the validity of a linear regression model. (2) Assumption Of No Autocorrelation. (3) Why No Autocorrelation Is Important? (4) Common Causes Of Autocorrelation. Omitted Variables: Missing important predictors

Read More