Let Y be a random variable. Then var(Y)equals
A) $\sqrt { \left. E \left[ Y - \mu _ { y } \right) ^ { 2 } \right] }$
B) $E \left[ \left| \left( Y - \mu _ { y } \right) \right| \right]$
C) $E \left[ \left( Y - \mu _ { y } \right) ^ { 2 } \right]$
D) $E [ ( Y - \mu ) ]$

Question

Quizplus · Accepted Answer

The variance of a random variable Y, denoted as var(Y), is defined as the expected value of the squared deviation of Y from its mean $\mu_y$, which is mathematically represented as $E \left[ \left( Y - \mu _ { y } \right) ^ { 2 } \right]$.

Let Y Be a Random Variable E[Y−μy)2]\sqrt { \left. E \left[ Y - \mu _ { y } \right) ^ { 2 } \right] }E[Y−μy​)2]​

Let Y Be a Random Variable $\sqrt { \left. E \left[ Y - \mu _ { y } \right) ^ { 2 } \right] }$