  We present a simple algorithm that estimates the cardinality $n$ of a set $V$
when allowed to sample elements of $V$ uniformly and independently at random.
Our algorithm with probability $(1-\delta)$ returns a
$(1\pm\epsilon)-$approximation of $n$ drawing $O\big(\sqrt{n} \cdot
\epsilon^{-1}\sqrt{\log(\delta^{-1})}\big)$ samples (for
$\epsilon^{-1}\sqrt{\log(\delta^{-1})} = O(\sqrt{n})$).
