How Can I Prove the Independence of Functions of Independent Random Variables?

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To prove that functions of independent random variables remain independent, one must show that the joint distribution of U = g(X) and V = h(Y) can be expressed as the product of their marginal distributions. The discussion emphasizes that if X and Y are independent, then their joint probability density function can be separated into the product of the functions of each variable. For continuous random variables, this involves using double integrals to demonstrate the independence, while for discrete variables, probabilities are used instead. Participants express confusion over notation and the correct mathematical representation but agree on the foundational concept that independence is preserved through the functions g and h. Clarifying these mathematical notations and steps is essential for a complete proof.
franz32
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Hello, I need some help on the independence of random variables...
"How do I prove that if X and Y are two independent random variables, then U=g(X) and V = h(Y) are also independent?"

- Isn`t that if random variables X and Y are independent, it implies
that f(x,y) = g(x)h(y) and vice versa? Also, note that g(x) and h(y) are
two marginals. But what I don`t understand is that what does it mean to
have U = g(X) to be a capital "X"?

- {then U=g(X) and V = h(Y) are also independent} what am I supposed to
show in this proof? And lastly, what is my first step/strategy in proving
this? Hope you can give me hints.. =)
 
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U is g of the random variable X. You do this all the time, such as when working out the variance: it is
E(X^2)-E(X)^2, So there's a function of a random variable there (X^2).

Are these continuous of discrete R.V.'s? Not that it matters two much. If it 's continuous look at the pdf of the joind dist. since g is a function of X alone, and h a function of Y alone the double integrals INT dxdy split as int dx int dy. If discrete replace integrals with sums.
 
Sir matt grime/anyone... =]
I hope someone can guide me.
I want to prove first the continuous. So, the joint pdf can be described as

f[g(X),h(Y)] = INTaINTb g(x)h(y) dx dy -> am I right here?
where a and b are arbitrary intervals.
= INTa h(y) [INTb g(x)dx] dy -> h(y) is treated as a constant.
= [INTb g(x)dx] [INTa h(y)dy] -> [INTb g(x)dx] is now a constant
= g(X) h(Y)

I believe I got screwed up in my notations... is this the proof? I hope it is.. but can someone help me edit this... will I use u's and v's here?... I think not.

For the discrete case...

f(g(X), h(Y)) = P(U = g(X), V = h(Y)) = P(U = g(X)) P(V = h(Y)) = g(X)h(Y)?

Is this the right proof? I hope someone can help me.. =]
 
franz32 said:
f[g(X),h(Y)] = INTaINTb g(x)h(y) dx dy -> am I right here?
where a and b are arbitrary intervals.
= INTa h(y) [INTb g(x)dx] dy -> h(y) is treated as a constant.
= [INTb g(x)dx] [INTa h(y)dy] -> [INTb g(x)dx] is now a constant
= g(X) h(Y)

I believe you made a mistake here, it's not

f[g(X),h(Y)] = g(x) \cdot h(y)

but it's

<br /> <br /> f(X,Y) = g(x) \cdot h(y)<br /> <br />

You were on the right track, but it should be

f(U,V) = g(U)h(V) = g(g(x)) \cdot h(h(y))

I believe that U and V (g(x) and h(y), respectively) should be independent since Y cannot influence g(x) and X cannot influence h(y) since X and Y are independent. I just don't know how to prove it in mathematical notation, but it's worth a try =)
 
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