Consider the multiple regression model with two regressors X1 and X2, where both variables are determinants of the dependent variable. You first regress Y on X1 only and find no relationship. However when regressing Y on X1 and X2, the slope coefficient of X1changes by a large amount. This suggests that your first regression suffers from

A. heteroskedasticity
B. perfect multicollinearity
C. omitted variable bias
D. dummy variable trap