Answer:
d. exists if the omitted variable is correlated with the included regressor and is a determinant of the dependent variable.
Explanation:
Omitted-variable bias exists when one or more germane variables are left out of a statistical model, and this bias bring about a situation whereby the estimated effects of the variables included in the model are attributed to the impact of the missing variables.
This usually happens when the form and data used for other parameters in the regression model that is estimated are not appropriate.