if x,y are independent, identically distributed r.v.-s with mean u and variance sigma^2 , find E[(X-Y)^2].

have tried but dont know how you could use x-y

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- Nov 3rd 2010, 09:43 AMeleahyfind E[(X-Y)^2] difficult to work out
if x,y are independent, identically distributed r.v.-s with mean u and variance sigma^2 , find E[(X-Y)^2].

have tried but dont know how you could use x-y - Nov 3rd 2010, 10:09 AMDinkydoe
$\displaystyle E[(X-Y)^2]= E[X^2-2XY+Y^2]= E[X^2]-2E[XY]+E[Y^2] $

Now use that E[XY]=E[X]E[Y] ...since X,Y are independant. - Nov 3rd 2010, 10:50 AMeleahyconfused
im a little confused..... i thought the question asked to find that formula using the fact mean is u and variance is sigma squared. Im probably wrong just dont know how to finish question ...thanks so much for taking time!!!

- Nov 3rd 2010, 12:00 PMharish21
$\displaystyle E(X) = \mu_{x}$

$\displaystyle Var(X) = E[X^2] - (E[X])^2 = E[X^2] - \mu_{x}^2$ - Nov 3rd 2010, 12:26 PMeleahy
Ok trying figure this out I can't figure how you get to E(x-y)^2 I'm not sure am I just missing something simple or how you get it. Workin on it but getting no where. Is E(x-y)^2 a specific formula??

- Nov 3rd 2010, 12:49 PMharish21
Look at post no. 2 by

**DinkyDoe**. It has already been found out for you! - Nov 3rd 2010, 12:51 PMeleahy
He seemed to multiply out then simplify , do I use your info before this I'm failing to see the connection sorry thanks for helpin ;)

- Nov 3rd 2010, 01:07 PMharish21
Follow his instructions first, and then use my info!