If the Three Least Squares Assumptions Hold, Then the Large $\widehat { \beta } _ { 1 }$

If the three least squares assumptions hold, then the large sample normal distribution of $\widehat { \beta } _ { 1 }$ is

A) $N \left( 0 , \frac { 1 } { n } \frac { \left. \operatorname { var } \left[ X _ { i } - \mu _ { X } \right) u _ { i } \right] } { \left[ \operatorname { var } \left( X _ { i } \right) \right] ^ { 2 } } \right)$
B) $N \left( \beta _ { 1 } , \frac { 1 } { n } \frac { \left. \operatorname { var } \left( u _ { i } \right) \right] ^ { 2 } } { \left[ \operatorname { var } \left( X _ { i } \right) \right] ^ { 2 } } \right)$
C) $N \left( \beta _ { 1 } , \frac { \sigma _ { u } ^ { 2 } } { \sum _ { i = 1 } ^ { n } \left( X _ { i } - \bar { X } \right) ^ { 2 } } \right.$
D) $N \left( \beta _ { 1 } , \frac { 1 } { n } \frac { \left. \operatorname { var } \left( u _ { i } \right) \right] } { \left[ \operatorname { var } \left( X _ { i } \right) \right] ^ { 2 } } \right)$