The residuals in a simple linear regression model should be randomly distributed. This is referred to as the assumption of ________.
- autocorrelation
- heteroscedasticity
- independence
- multicollinearity
The assumption of independence in simple linear regression implies that the residuals (errors) between the observed and predicted values are not correlated. That is, the error value for one observation does not depend on the error value of any other observation. This is typically checked by examining a plot of the residuals for any visible pattern.
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