The following seems to hold in numerical simulations, is it true? $$\lim_{n\to \infty} \int_0^1 dx \frac{n! 2^{-n} n}{(n x)!(n-n x)!\sqrt{x(1-x)}}=2$$
It's a combination of two known integrals
$$\lim_{n\to \infty} \int_0^1 dx \frac{n! 2^{-n} n}{(n x)!(n-n x)!\}=1$$
$$\int_0^1 dx \frac{1}{\sqrt{x(1-x)}}=\pi$$
First one follows from asymptotic expansion of Gamma and the second is done using trig substitution
Edit: $x!$ is short for $\Gamma(x+1)$.
Limit convergence is apparent for $n$ between 10 and $10^6$, $\log_{10} n$ gives an almost perfect fit to the log of deviation
Motivation -- the last integral is an instance of "Information Volume", an estimate of number of statistically distinguishable distributions in the Bernoulli model, used as a measure of model complexity . A major annoyance is that this integral fails to exist for some popular models, like the geometric distribution family. Perhaps we can fix this by instead estimating the number of observation sequences that are well fit by some distribution in the model? That's the first integral.