Let $X_n$ a random variable of same law

In summary, the conversation discusses a question about proving the convergence of two expressions involving random variables with the same law. The suggested approach involves setting a new variable and proving its discrete probability density.
  • #1
Feynman
159
0
:confused: Hello

I have a simple question :
Let $X_n$ a random variable of same law
If $V(X_n)\longrightarrow 0$ when $n\longrightarrow +\infty$
How schow that : $E(X_n)\longrightarrow C$ and $E(X_{n}^{2}\longrightarrow C^2$ and C is a constant?
Thanks
 
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  • #2
Hello

[tex]

I have a simple question :
Let $X_n$ a random variable of same law
If $V(X_n)\longrightarrow 0$ when $n\longrightarrow +\infty$
How schow that : $E(X_n)\longrightarrow C$ and $E(X_{n}^{2}\longrightarrow C^2$ and C is a constant?
Thanks
[/tex]
 
  • #3
Feynman, LaTex is down at the moment.
 
  • #4
How far have you got with this one Feynman?

I suggest you let z = x - E(x) and then prove that E( z^2 ) = 0 implies that Z has a discrete probability denstiy with P(z=0) = 1.
 

FAQ: Let $X_n$ a random variable of same law

What is a random variable?

A random variable is a variable that takes on numerical values as outcomes of a random phenomenon. It represents the possible outcomes of a specific experiment or event, and its value is determined by chance.

What does it mean for two random variables to have the same law?

When two random variables have the same law, it means that they have the same probability distribution. This means that they have the same set of possible outcomes and the same probabilities associated with each outcome.

How is the law of a random variable determined?

The law of a random variable is determined by its probability distribution, which specifies the probabilities of each possible outcome. This can be determined through empirical observations or mathematical models.

What is the significance of $X_n$ in the phrase "Let $X_n$ a random variable of same law"?

$X_n$ represents a sequence of random variables with the same law. This notation is often used in statistics and probability to denote a series of related random variables.

Can two random variables have the same law but different values?

Yes, two random variables can have the same law but different values. This means that they have the same probability distribution, but their individual outcomes may differ. For example, two fair dice have the same probability distribution (the law), but their individual outcomes may be different.

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