Conditional expectation and expected value

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Given the joint distribution $f(x,y) = {x \choose y} (\frac{1}{2})^x \frac{x}{20}$ where $y=0,1,2 \cdots x$ and $x=2,3,4,5,6$. Find $E(y\mid x)$ and $E(y)$

Wondering if I am missing something.

Using Binomial identity and direct definition of $f(x)$ (the limit was from the plot I made):

$f(x) = (\frac{1}{2})^x \frac{x}{20} \sum_{y=0}^x {x \choose y} =(\frac{1}{2})^x \frac{x}{20} 2^{x} = \frac{x}{20} $

Use $f(x)$ to compute $f(y\mid x)$, given that the joint distribution is given:

So that $f(y\mid x) = \frac{f(x,y)} {f(x)} = \frac{ {x \choose y} (\frac{1}{2})^x \frac{x}{20}}{ \frac{x}{20}} = {x \choose y} 2^{-x} $

$E(y \mid x) = \sum_{y=0}^{x} y f(y\mid x) = 2^{-x} \sum_{y=0}^{x} {x \choose y} y $

Then: Using the identity : $ \sum_{y=0}^{x} {x \choose y} y = x 2^{x-1} $

$E(y \mid x) = \sum_{y=0}^{x} y f(y\mid x) = 2^{-x} \sum_{y=0}^{x} {x \choose y} y = x (2^{-x} \cdot 2^{x-1}) = \frac{x}{2} $

Does this makes sense?

How does $E(y)$ follows, I guess $E(y) = E(E(y \mid x))$

$E(y) = E(E(y \mid x))$

$E(y) = E(E(y \mid x)) = \sum_{x=2}^6 \frac{x}{20} (2^{-x} \sum_{y=0}^{x} {x \choose y} y) = \frac{1}{40}\sum_{x=2}^6 x^2 $

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The easiest way to proceed is to observe that your joint pmf is

$$p(x,y)=p(y|x)p(x)=\binom{x}{y}\left(\frac{1}{2}\right)^x\times\frac{x}{20}$$

Thus $(Y|X=x)\sim Bin\left(x;\frac{1}{2}\right)$

And X is a discrete rv with support $x=\{2,3,4,5,6\}$ and pmf

$$p(X=x)=x/20$$

Thus

$$\mathbb{E}[Y|X=x]=x/2$$

And

$$\mathbb{E}[Y]=\mathbb{E}[\mathbb{E}[Y|X]]= \mathbb{E}[X/2]= \frac{1}{2 }\mathbb{E}[X] = \frac{1}{2 }\times\frac{9}{2}=\frac{9}{4}$$