The mean and variance of eight observations are $9$ and $9.25,$ respectively. If six of the observations are $6,7,10,12,12$ and $13,$ find the remaining two observations.
Let the remaining two observations be $x$ and $y$.
Therefore, the observations are $6,7,10,12,12,13, x, y$
Mean, $\bar{x}=\frac{6+7+10+12+12+13+x+y}{8}=9$
$\Rightarrow 60+x+y=72$
$\Rightarrow x+y=12$ ...........$(1)$
Variance $ = 9.25 = \frac{1}{n}\sum\limits_{i = 1}^8 {{{\left( {{x_i} - \bar x} \right)}^2}} $
$9.25=\frac{1}{8}[(-3)^{2}+(-2)^{2}+(1)^{2}+(3)^{2}+(4)^{2}$
$+x^{2}+y^{2}-2 \times 9(x+y)+2 \times(9)^{2}]$
$9.25=\frac{1}{8}\left[9+4+1+9+9+16+x^{2}+y^{2}-18(12)+162\right]$ ........[ using $(1)$ ]
$9.25=\frac{1}{8}\left[48+x^{2}+y^{2}-216+162\right]$
$9.25=\frac{1}{8}\left[x^{2}+y^{2}-6\right]$
$\Rightarrow x^{2}+y^{2}=80$ .........$(2)$
From $(1),$ we obtain
$x^{2}+y^{2}+2 x y=144$ ........$(3)$
From $(2)$ and $(3),$ we obtain
$2 x y=64$ ..........$(4)$
Subtracting $(4)$ from $(2),$ we obtain
$x^{2}+y^{2}-2 x y=80-64=16$
$\Rightarrow x-y=\pm 4 $ ...........$(5)$
Therefore, from $(1)$ and $(5),$ we obtain
$x=8$ and $y=4,$ when $x-y=4$
$x=4$ and $y=8,$ when $x-y=-4$
Thus, the remaining observations are $4$ and $8$
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Mean and standard deviation of 100 items are 50 and $4,$ respectively. Then find the sum of all the item and the sum of the squares of the items.
If the mean and variance of eight numbers $3,7,9,12,13,20, x$ and $y$ be $10$ and $25$ respectively, then $\mathrm{x} \cdot \mathrm{y}$ is equal to
If $\mathop \sum \limits_{i = 1}^9 \left( {{x_i} - 5} \right) = 9$ and $\mathop \sum \limits_{i = 1}^9 {\left( {{x_i} - 5} \right)^2} = 45,$ then the standard deviation of the $9$ items ${x_1},{x_2},\;.\;.\;.\;,{x_9}$ is :
A data consists of $n$ observations
${x_1},{x_2},......,{x_n}.$ If $\sum\limits_{i - 1}^n {{{({x_i} + 1)}^2}} = 9n$ and $\sum\limits_{i - 1}^n {{{({x_i} - 1)}^2}} = 5n,$ then the standard deviation of this data is