The errors in a regression model are assumed to have an increasing mean.

Name: The errors in a regression model are assumed to have an increasing mean.
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In regression analysis, the errors are assumed to have constant mean and constant variance, which is known as homoscedasticity. If the errors have an increasing or decreasing mean, it violates the assumption of homoscedasticity and may lead to biased and inefficient estimates.

The Errors in a Regression Model Are Assumed to Have