Almost sure pointwise inequality between conditional variance and variance or between conditional expectation and expectation I have a question about conditional expectation and conditional variance. It's a very general question. We defined conditional variance by
$$ \operatorname{Var}(X|\mathcal{F}):=E((X-E(X|\mathcal{F}))^2|\mathcal{F}) $$
For a random variable $ X $ and a $\sigma$-algebra $ \mathcal{F}$. Are there any inequalities such that
$ \operatorname{Var}(X|\mathcal{F})\le \operatorname{Var}(X)$ or $ \operatorname{Var}(X|\mathcal{F})\ge \operatorname{Var}(X)$ and the same question for the conditional expectation: 
$E(X|\mathcal{F}) \le E(X)$ or $ E(X|\mathcal{F}) \ge E(X)$ 
Are any one of them true in general, or what further assumption have to bee assumed that a conclusion as above is true? Often such an inequality would be very usful. 
Thanks in advance.
hulik

None of these inequalities are true in general.
Suppose you have 


*

*$\Pr(X=0,Y=0) = \frac{1}{5}$

*$\Pr(X=0,Y=1) = \frac{1}{5}$

*$\Pr(X=2,Y=1) = \frac{1}{5}$

*$\Pr(X=-5,Y=2) = \frac{1}{5}$

*$\Pr(X=3,Y=2) = \frac{1}{5}$


Then defining $\mathcal{F}$ on values of $Y$
we have $E[X]=0$, $E[X|Y=1]=1$, $E[X|Y=2]=-1$, 
and $Var(X)=7.6$, $Var(X|Y=0)=0$, $Var(X|Y=2)=16$.
