  A {\em leader election} algorithm is an elimination process that divides
recursively into tow subgroups an initial group of n items, eliminates one
subgroup and continues the procedure until a subgroup is of size 1. In this
paper the biased case is analyzed. We are interested in the {\em cost} of the
algorithm, i.e. the number of operations needed until the algorithm stops.
Using a probabilistic approach, the asymptotic behavior of the algorithm is
shown to be related to the behavior of a hitting time of two random sequences
on [0,1].
