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Question: If X is a random passion variate such that \[E({X^2}) = 6\], then \(E(X) = \) A.-3 B.2 C.-3 & ...

If X is a random passion variate such that E(X2)=6E({X^2}) = 6, then E(X)=E(X) =
A.-3
B.2
C.-3 & 2
D.-2

Explanation

Solution

Let xx will be the average number of the occurrence of success events in a particular time in the poisson distribution. Then the mean and variance of the variable are equal i.e.
Var(X)=E(X)=x\Rightarrow Var(X) = E(X) = x
And put this value in the formula of variance which is given by
Var(X)=E(X2)[E(X)]2\Rightarrow Var(X) = E({X^2}) - {\left[ {E(X)} \right]^2}

Complete step-by-step answer:
The probability distribution in which probability of a variable expressed the events occurring in a fixed interval of time or space and these events occur with a constant mean rate is known as poison distribution and it is a discreate probability distribution.
In this question let us see what is given? We are given with the value of E(X2)E({X^2})i.e.
E(X2)=6\Rightarrow E({X^2}) = 6 ………..(1)
And we have to find the value of E(X)E(X)i.e. mean of the variable.
First of all, let us assume the value of E(X)E(X)be xxi.e.xx
E(X)=x\Rightarrow E(X) = x …………(2)
In the poison distribution the mean and variance of variable X both are equal i.e.
Var(X)=E(X)\Rightarrow Var(X) = E(X) ………….(3)
From (2) and (3) we get,
Var(X)=x\Rightarrow Var(X) = x ………….(4)
variance is given by expected value of the squared difference between the variable and its expected value i.e.
Var(X)=E([XE(X)]2)\Rightarrow Var\left( X \right) = E\left( {{{\left[ {X - E\left( X \right)} \right]}^2}} \right)
By simplifying it we get,
Var(X)=E(X2)[E(X)]2\Rightarrow Var\left( X \right) = E\left( {{X^2}} \right) - {\left[ {E\left( X \right)} \right]^2} …………(5)
Put the value of (1), (2) and (3) in equation (5), we get,
x=6[x]2\Rightarrow x = 6 - {\left[ x \right]^2}
By opening the bracket, we get,
x=6x2\Rightarrow x = 6 - {x^2}
Taking all the terms on L.H.S, we get,
x2+x6=0\Rightarrow {x^2} + x - 6 = 0
Solve the above quadratic equation by finding factors of 6 i.e. 2 and 3 and when we take this combination and by subtracting them, we get 1. Hence, we can write the term of xxas x=3x2xx = 3x - 2xand putting the value in the above equation, we will get,
x2+3x2x6=0\Rightarrow {x^2} + 3x - 2x - 6 = 0
Taking common 3 from first two terms and -2 from last two terms we get,
x(x+3)2(x+3)=0\Rightarrow x\left( {x + 3} \right) - 2\left( {x + 3} \right) = 0
Taking x+3x + 3 common from both terms, we get,
(x2)(x+3)=0\Rightarrow \left( {x - 2} \right)\left( {x + 3} \right) = 0
Therefore, x2=0x - 2 = 0 and x+3=0x + 3 = 0
Hence, x=2x = 2 and x=3x = - 3
Therefore, the correct answer is option C.

Note: Mean and variance of poisson distribution:
We can prove that in poisson distribution mean and variance are equal.
The probability mass function i.e. pmf of the poisson distribution is given by
P(x)=λx.eλx!\Rightarrow P\left( x \right) = \dfrac{{{\lambda ^x}.{e^{ - \lambda }}}}{{x!}}, where xxis 0,1,2,3…….\infty
Mean i.e. E(x)E(x) can be calculated as
E(x)=x=0xP(x)\Rightarrow E\left( x \right) = \sum\limits_{x = 0}^\infty {xP\left( x \right)}
Put the value of P(x)P\left( x \right) in this equation, we get,
E(x)=x=0xλx.eλx!\Rightarrow E\left( x \right) = \sum\limits_{x = 0}^\infty {x\dfrac{{{\lambda ^x}.{e^{ - \lambda }}}}{{x!}}}
By solving this equation, we will get,
E(x)=λ\Rightarrow E\left( x \right) = \lambda
Now find E(x(x1))E\left( {x\left( {x - 1} \right)} \right) and we will get this value of this i.e.
E(x(x1))=λ2\Rightarrow E\left( {x\left( {x - 1} \right)} \right) = {\lambda ^2}
Now, E(x2)=E(x(x1))+E(x)E\left( {{x^2}} \right) = E\left( {x\left( {x - 1} \right)} \right) + E\left( x \right) and putting the value of E(x(x1))E\left( {x\left( {x - 1} \right)} \right) and E(x)E(x) in this equation we get,
E(x2)=λ2+λ\Rightarrow E\left( {{x^2}} \right) = {\lambda ^2} + \lambda
As we know,
Var(X)=E(X2)[E(X)]2\Rightarrow Var\left( X \right) = E\left( {{X^2}} \right) - {\left[ {E\left( X \right)} \right]^2}
And putting the value of E(x)E(x) and E(x2)E\left( {{x^2}} \right), we get,
Var(X)=λ2+λ(λ)2\Rightarrow Var\left( X \right) = {\lambda ^2} + \lambda - {\left( \lambda \right)^2}
Hence, Var(X)=λVar\left( X \right) = \lambda
Therefore, in poisson distribution mean and variance are equal. Hence, proved.