If `overline X` is the mean of a distribution of `X,` then under usual notation sum `sum_(i=1)^n f_i (x_2-overlinex)` is

If m is mean of distribution, then sum(x_(i) - m) is equal to

If m is mean of distribution, then sum(x_(i) - m) is equal to

If overlinex is the mean of a set of n observations x_1 , x_2 , x_3…..,x_n then sum_(i=1)^n(x_i-overlinex) is equal to

If overlineX_(1),overlineX_(2) are the means of two distributions such that overlineX_(1)ltoverlineX_(2)andoverlineX is mean of the combined distribution , then

If overline (x_(1)) " and " overline (x_(2)) are the means of two distributions such that overline (x_(1)) lt overline (x_(2)) " and " overline (x) is the mean of the combined distriubtion, then

If overline (x_(1)) " and " overline (x_(2)) are the means of two distributions such that overline (x_(1)) lt overline (x_(2)) " and " overline (x) is the mean of the combined distriubtion, then

If barx represents the mean of n observations x_1, x_2,…….,x_n , then value of sum_(i=1)^n (x_1-barx) is :