  The missing mass refers to the probability of elements not observed in a
sample, and since the work of Good and Turing during WWII, has been studied
extensively in many areas including ecology, linguistic, networks and
information theory.
  This work determines what is the \emph{maximal variance of the missing mass},
for any sample and alphabet sizes. The result helps in understanding the
missing mass concentration properties.
