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# If variance of $x_1, x_2,....x_n$ is $\sigma^2$ then variance of $ax_1, ax_2,.....ax_n ( a \neq 0)$ is

$\begin {array} {1 1} (A)\;\sigma^2 & \quad (B)\;a \sigma^2 \\ (C)\;a^2 \sigma^2 & \quad (D)\;\large\frac{\sigma^2}{a^2} \end {array}$

$\sigma^2= \large\frac{1}{n}$ $\Sigma (x-\overline x)^2$
New variance = $\large\frac{1}{n}$ $\Sigma ( ax - a \overline x)^2$
$= a^2\sigma^2$
Ans : (C)