Each of the Following Is Key Assumptions About the Error $\varepsilon$

Each of the following is key assumptions about the error term in a regression model, except:

A) Error variance is not constant (heteroscedasticity)
B) The expected value of the errors is 0: E( $\varepsilon$ _i) = 0
C) Errors are mutually independent: The correlation of $\varepsilon$ _i with $\varepsilon$ _j is zero
D) Errors are uncorrelated with any X