In multiple regression, the mean of the probability distribution of the error variable $\epsilon$ is assumed to be:
A. Any value greater than 1
B. $k$,where $k$ is the number of independent variables included in the model
C. 0.0
D. 1.0

When the independent variables are correlated with one another in a multiple regression analysis, this condition is called:
A. multicollinearity
B. elasticity
C. heteroscedasticity
D. homoscedasticity