The problem:
X is a binomial random variable, find $E[\frac{1}{X+1}]$ n and p are not given
PDF for a binomial distribution is $\binom{n}{k}p^k(1-p)^{n-k}$
Expected value is $\sum{x_ip(x_i)}$
But this is where I get stuck, I'm really rusty on my statistics and I'm not sure exactly how to structure it in the next step? I think I want to get the form of the following out of the summation
$\sum _{k=0}^{n} \binom{n}{k}p^k(1-p)^{n-k} = (p + 1 - p)^n = 1$
But I'm not sure if it should look like
$\sum \frac{1}{xp(x)+1} $
and if it should where to go from here?
By definition of Expectation, $\mathbb{E}(\frac{1}{1+X})$ should look like $\sum \frac{1}{1+x}\cdot p(x)$. In fact, $$\mathbb{E}(\frac{1}{1+X})=\sum_{k=0}^{n}\frac{1}{1+k}\cdot {n \choose k}p^k(1-p)^{n-k}=\frac{1}{(n+1)p}\cdot \sum_{k=0}^{n}{n+1 \choose k+1}\cdot p^{k+1}(1-p)^{n-k}=\frac{1}{(n+1)p}\cdot(1-(1-p)^{n+1}) $$