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3. (5 points) Which of the following can cause OLS estimators to be biased? Explain. (a) A sample correlation coefficient of 0.99 between two independent variables both included in the model. (b) When one independent variable can be expressed as an exact linear function of two or more of the other independent variable: (c) Omitting an important variable that is correlated with other independent variables in a model (a) High correlation coefficient (0.99) does not violate Assumption 4 so that Assumption 4 (no perfect collinearity) still holds. (b) Violates Assumption 4. (c) Violates Assumption 3 (zero conditional mean) Thus, b & c causes OLS estimators to be biased!1. (4 points) Which of the following can cause OLS estimators to be biased? You should list all answers and provide justification for your answer s) clearly. (a) Omitting an important variable that is correlated with other independent variables in a model. (b) Heteroskedasticity. (c) When one independent variable can be expressed as an exact linear function of two or more of the other independent variables. (d) A sample correlation coefficient of 0.99 between two independent variables both included in the model. (e) Detecting violation of normality. (f) When one independent variable is a constant multiple of another independent variable