If the difference between the expectation of the square of a random variable $[E (X^{2})]$ and the square of the expectation of the random variable $[E (x)]^{2}$ is denoted by R, then

R = 0

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R < 0

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R \geq 0

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R > 0

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Solution

The correct option is C $R \geq 0$
$R = E (x^{2}) - (E . (x))^{2}$
= Var (x)

$∵$ Variance can not be -ve so $R \geq 0$

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If the difference between the expectation of the square of a random variable [E(X2)] and the square of the expectation of the random variable [E(x)]2 is denoted by R, then

The correct option is C R≥0 R=E(x2)−(E.(x))2 = Var (x) ∵ Variance can not be -ve so R≥0

If the difference between the expectation of the square of a random variable $[E (X^{2})]$ and the square of the expectation of the random variable $[E (x)]^{2}$ is denoted by R, then

The correct option is C $R \geq 0$
$R = E (x^{2}) - (E . (x))^{2}$
= Var (x)

$∵$ Variance can not be -ve so $R \geq 0$