The mean square deviation of a set of observation `x_(1), x_(2)……x_(n)` about a point m is defined as `(1)/(n)Sigma_(i=1)^(n)(x_(i)-m)^(2)`. If the mean square deviation about `-1 and 1` of a set of observation are 7 and 3 respectively. The standard deviation of those observations is

The mean square deviations of a set of observations x_(1),x_(2), …, x_(n) about a point c is defined to be (1)/(n) sum_(i=1)^(n)(x_(i)-c)^(2) . The mean square deviations about -1 and +1 of a set of observations are 7 and 3, repectively. Find the standard deviation of this set of observations.

If mean of squares of deviations of a set of n observations about - 2 and 2 are 18 and 10 respectively,then standard deviation of this set of observations is

The mean square deviation of a set of m observations y_1, y_2…..y_m about a point K is defined as 1/m sum_(i = 1)^(m) (y_i - k)^(2) . The mean square deviation about -3 and 3 are 16 and 8 respectively, then standard deviation of this set of observation?

Mean deviation for n observation x_(1),x_(2),…..x_(n) from their mean bar x is given by

Mean deviation for n observation x_(1),x_(2),…..x_(n) from their mean bar x is given by

Mean deviation for n observations x_(1), x_(2),….., x_(n) from their mean bar(x) is given by :

The mean and standard deviation of a set of n_1 observation are barx_1 and S_1 , respectively while the mean standard deviation of another set of n_2 observations are barx_2 and S_2 , respectively . Show that the standard deviation of the combined set of (n_1+n_2) observations is given by standard deviation sqrt ((n_1(S_1)^2 + n_1(S_2)^2)/(n_1+n_2) + (n_1+n_2 (barx_1 - barx_2)^2)/(n_1-n_2)^2)