A crucial assumption in a regression model is that the error term is not correlated with any of the explanatory variables.

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This assumption is known as the assumption of no autocorrelation or, more commonly, the assumption of no correlation between the error term and the independent variables. This is important because if this assumption is violated, it can lead to biased and inconsistent estimates of the regression coefficients, and can also affect statistical inference and prediction.

A Crucial Assumption in a Regression Model Is That the Error