Let $Y : (\Omega , \mathcal A,\Bbb P) \to \Bbb R$ a discrete variable and $A\in\mathcal A$, $P(A)\neq 0$, how can you prove only using elementary definitions the following: $$\frac{\Bbb E(Y1_A)}{\Bbb E(1_A)}=\sum_y y\frac{\Bbb P(A, Y=y)}{P(A)}$$
What I know is : $$E(1_A)=P(A)$$ and $$\Bbb E(Y) = \int_\Omega {Y(\omega) d\Bbb P (\omega)}=\int_\Bbb R{yd\Bbb P_Y(y)}=\sum_yy\Bbb P(Y=y)$$
(I am aware the denominators in both sides simplify but I leave it like that, as this is a formula used in the context of an introduction to conditional expectation.)
By the Law of Total Expectation
$$\Bbb E(Y1_A)=\sum_{y}\Bbb E(Y1_A\mid Y=y)P\{Y=y\}$$ $$=\sum_{y}\Bbb yP\{A\mid Y=y\}P\{Y=y\}=\sum_{y}\Bbb yP\{A, Y=y\}$$
or
$$\Bbb E(Y1_A)=\sum_{y}\Bbb E(Y1_{A\cap\{Y=y\}})=\sum_{y}\Bbb yP\{A, Y=y\}$$