Probability: Proof of E[X/X+Y]=(X+Y)/2, X and Y are i.i.d. r.v.

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SUMMARY

The discussion centers on proving that for independent and identically distributed random variables X and Y, the expected value E[X/(X+Y)] equals (X+Y)/2. Participants highlight the confusion surrounding the transformation of E[X] into a function of random variables and emphasize that E[X/(X+Y)] + E[Y/(X+Y)] equals 1 for normalized distributions. The proof relies on recognizing that both E[X/(X+Y)] and E[Y/(X+Y)] must equal 1/2 due to symmetry. A suggested approach involves using power series to define the reciprocal of random variables.

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Homework Statement


Given that X and Y are i.i.d. r.v, and E[X]<infinity.
Any idea how to prove that E[X/X+Y]=E[Y/X+Y]=(X+Y)/2?


Homework Equations





The Attempt at a Solution


I know that E[X] or E[Y] are constants, how come it now says E[X/X+Y] = (X+Y)/2 which is a r.v.?
and for X and Y being independent, E[XY]=E[X]E[Y], but now it is E[X/X+Y], which I think it means E[X/(X+Y)], the upper and lower aren't independent, we cannot write E[X]/E[X+Y]...no idea where to begin with.

Any help is appreciated.
 
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This seems weird to me, both for the reason you mention, that ##E[f(X,Y)]## can't be a function of the random variables, and also because you can easily show that

$$ E[X/(X+Y)] + E[Y/(X+Y)] = 1$$

for a normalized distribution. So the only way we can have ##E[X/(X+Y)] = E[Y/(X+Y)]## is if they are both 1/2.

Aside from those concerns, one way to approach the reciprocal of a random variable is through a power series. Namely, given a random variable ##X##, we can define a new random variable ##X'## by

$$ X = \bar{X} + X',~~~~ E[X']=0,$$

where ## \bar{X} = E[X]##. Then, if ##\bar{X}\neq 0##, we can use the geometric series to define

$$ \frac{1}{X} = \frac{1}{\bar{X}} \sum_{n\geq 0} (-1)^n \left( \frac{X'}{\bar{X}} \right)^n ,$$

which is convergent if ##|X'| \leq |\bar{X}|##. A similar construction would serve to define ##1/(X+Y)## or similar rational functions.

If you weren't already given a seemingly misleading answer to the question, this is the approach I would suggest.
 
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