If the mean and `S.D.` of `n` observations `x_1,x_2......x_n` are `x` and `σ` resp, then the sum of squares of observations is

If the mean of n observations x_1,x_2,x_3...x_n is barx then the sum of deviations of observations from mean is

If the mean of n observations x_(1),x_(2),x_(3)...x_(n) is bar(x) then the sum of deviations of observations from mean is

If the S.D. of n observations x_1,x_2,x_3.......x_n is 4.and another set of n observations y_1,y_2.y_3......y_n ,is 3 the S.D. of n observations x_1-y_1,x_2-y_2,x_3-y_3......................x_n-y_n is

If the mean of a set of observations x_(1),x_(2), …,x_(n)" is " bar(X) , then the mean of the observations x_(i) +2i , i=1, 2, ..., n is

If the mean of a set of observations x_(1),x_(2), …,x_(n)" is " bar(X) , then the mean of the observations x_(i) +2i , i=1, 2, ..., n is

If the mean of a set of observations x_(1),x_(2), …,x_(n)" is " bar(X) , then the mean of the observations x_(i) +2i , i=1, 2, ..., n is

Given that bar x is the mean and sigma^2 is the variance of n observations x_1, x_2, ... x_n . Prove that the mean and variance of the observations ax_1, ax_2, ... ,ax_n , are a bar x and a^2 sigma^2 respectively (a ne 0) .

Given that bar x is the mean and sigma^2 is the variance of n observations x_1 , x_2 ,.... x_n . Prove that the mean and variance of the observations ax_1, ax_2, ax_3 ,......, ax_n are a bar x and a^2 sigma^2 , respectively, (a ne 0) .

Given that bar x is the mean and sigma^2 is the variance of n observations x_1x_2 , ..., x_n . Prove that the mean and variance of the observations a x_1,""""a x_2 , a x_3,""""dot""""dot""""dot"""",""a x_n are a bar x and a^2sigma^2 ,

Given that bar x is the mean and sigma^2 is the variance of n observations x_1x_2 , ..., x_n . Prove that the mean and variance of the observations a x_1,a x_2 , a x_3,dotdotdot,a x_n are a bar x and a^2sigma^2 ,