Find Cov(Z,W) with E(X^2)if X is N(0,1)

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Let X and Y be two independent [tex]\mathcal{N}(0,1)[/tex] random variables and

[tex]Z=1+X+XY^2[/tex]

[tex]W=1+X[/tex]
I want to find Cov(Z,W).

Solution:-

[tex]Cov(Z,W)=Cov(1+X+XY^2,1+X)[/tex]

[tex]Cov(Z,W)=Cov(X+XY^2,X)[/tex]

[tex]Cov(Z,W)=Cov(X,X)+Cov(XY^2,X)[/tex]

[tex]Cov(Z,W)=Var(X)+E(X^2Y^2)-E(XY^2)E(X)[/tex]

[tex]Cov(Z,W)=1+E(X^2)E(Y^2)-E(X)^2E(Y^2)[/tex]

[tex]Cov(Z,W)=1+1-0=2[/tex]

Now E(X)=0, So [tex]E(X)^2E(Y^2)=0[/tex], But i don't follow how [tex]E(X^2)E(Y^2)=1?[/tex] Would any member explain that? My another question is what is [tex]Var(X^2)?[/tex]
 
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Re: E(x^2)and VAR(x^2)if X is N(0,1).

Dhamnekar Winod said:
My another question is what is [tex]Var(X^2)?[/tex]

Hi Dhamnekar,

Let's start with this one.
It's the variance. It is the mean of the squared deviations from the average.
And the average of $X$ is the same thing as the expected value $E(X)$ or just $EX$.
In formula form:
$$\operatorname{Var}(X) = E\left((X - EX)^2\right)$$
If we write it out, we can find that it can be rewritten as:
$$\operatorname{Var}(X) = E(X^2) - (EX)^2$$

Dhamnekar Winod said:
Let X and Y be two independent [tex]\mathcal{N}(0,1)[/tex] random variables and

(snip)

Now E(X)=0, So [tex]E(X)^2E(Y^2)=0[/tex], But i don't follow how [tex]E(X^2)E(Y^2)=1?[/tex] Would any member explain that?

Now let's get back to your first question.

The fact that $X \sim \mathcal{N}(0,1)$ means that $\operatorname{Var}(X)=1$.
Combine it with $EX=0$ and fill it in:
$$\operatorname{Var}(X) = E(X^2) - (EX)^2 \implies 1=E(X^2)-0 \implies E(X^2)=1$$
 
Re: E(x^2)and VAR(x^2)if X is N(0,1).

Klaas van Aarsen said:
Hi Dhamnekar,

Let's start with this one.
It's the variance. It is the mean of the squared deviations from the average.
And the average of $X$ is the same thing as the expected value $E(X)$ or just $EX$.
In formula form:
$$\operatorname{Var}(X) = E\left((X - EX)^2\right)$$
If we write it out, we can find that it can be rewritten as:
$$\operatorname{Var}(X) = E(X^2) - (EX)^2$$
Now let's get back to your first question.

The fact that $X \sim \mathcal{N}(0,1)$ means that $\operatorname{Var}(X)=1$.
Combine it with $EX=0$ and fill it in:
$$\operatorname{Var}(X) = E(X^2) - (EX)^2 \implies 1=E(X^2)-0 \implies E(X^2)=1$$

Hello,
If $X$ be $\mathcal{N}(0,1)$ random variable, and $Y=X^2$ is the function of $X$, what is the distribution of $Y$?Is its distribution Normal?
 
Re: E(x^2)and VAR(x^2)if X is N(0,1).

Dhamnekar Winod said:
Hello,
If $X$ be $\mathcal{N}(0,1)$ random variable, and $Y=X^2$ is the function of $X$, what is the distribution of $Y$?

Is its distribution Normal?

No...

In probability theory and statistics, the chi-squared distribution (also chi-square or $χ^2$-distribution) with $k$ degrees of freedom is the distribution of a sum of the squares of $k$ independent standard normal random variables.​