# Independence relation between observation and error [duplicate]

Having a simple model like: Y = a + bX + u where u represent the error term, if I know that the observation of X and Y are i.i.d, also the error term is i.i.d?

• stats.stackexchange.com/questions/94872 answers the question about independence, because $u = Y-a-bX$ is a function of the iid variables $(X,Y).$ As far as whether the $u_i$ have identical distributions, perhaps you can answer that part of the question yourself?
– whuber
Dec 29, 2018 at 18:34
• @whuber ok, thank you, therefore is independent. Although is trivial I still have some doubt about identically distribution. Supposing that both X and Y are N(0,1) then u is N(-a,2). Therefore, are not identically distributed. is it correct? Dec 29, 2018 at 21:01
• If $X$ and $Y$ are both standard Normal, then perforce $a=0$ and $b=1$ and you must still conclude the $u_i$ are identically distributed.
– whuber
Dec 29, 2018 at 22:57
• @whuber The variance of the sum of two independent standard normal, should not be the sum of the variance of each r.v.? As a consequence u should not have a different variance? Dec 30, 2018 at 9:04
• You haven't supplied assumptions that imply $u$ is the sum of independent standard Normal variables.
– whuber
Dec 30, 2018 at 16:07