I've got this question that I'm really struggling with.
we have $X \sim N(\mu_X,\sigma^2)$, $Y \sim N(\mu_Y,\sigma^2)$
$S_X^2=$ $\sum_{i=1}^n (X_i-\overline X) \over (n-1) $, and $S_Y^2=$ $\sum_{i=1}^m (Y_i-\overline Y) \over (m-1) $
The pooled variance is $S_p^2=$ $(n-1)S_X^2+(m-1)S_Y^2\over n+m-2$
we also know that $S_X^2, S_Y^2, S_p^2$ are all unbiased estimators of $\sigma^2$.
We want to show that the pooled standard deviation $S_p = \sqrt {S_p^2}$ is a biased estimator of $\sigma$.
We're asked to start with the distribution of $S_p^2$, then show the bias of $S_p$
I started with $S_p^2=$ $(n-1)S_X^2+(m-1)S_Y^2 \over n+m-2$
$S_p=$ $\sqrt{(n-1)S_X^2+(m-1)S_Y^2 \over n+m-1}$
$\mathrm{E}(S_p)=$ $1 \over \sqrt{n+m-2}$ $\mathrm{E}(\sqrt{(n-1)S_X^2+(m-1)S_Y^2})$
I tried introducing $\sigma^2 \over \sigma^2$ into the equation, in order to get to $\chi^2$ and get the expected values from there, but I'm not able to get rid of the square root to get the expected values as $\chi^2$ values.
what's my mistake?
really appreciate your help.