Which of the following are true statements.
Variance gives a better picture of dispersion or scatter compared to mean deviation
Option A: As we take the square of deviations the greater deviations would be contributing more compared to the smaller deviations giving us a better picture than just adding all the deviations.
Option B: For given n observations x1, x2, ....xn with mean variance about mean would be
Option C: Variance is sum of squares of deviations. The only way it can be 0 is if all deviations are 0 which implies are observations are equal.
Option D: Variance can never be negative as it is the sum of squares. The least it can get is 0 and only in the case where all observations are equal.