  Can there be a `Litmus test' for determining the nature of transition in
models of percolation? In this paper we argue that the answer is in the
affirmative. All one needs to do is to measure the `growth exponent' $\chi$ of
the largest component at the percolation threshold; $\chi < 1$ or $\chi = 1$
determines if the transition is continuous or discontinuous. We show that a
related exponent $\eta = 1 - \chi$ which describes how the average maximal jump
sizes in the Order Parameter decays on increasing the system size, is the
single exponent that describes the finite-size scaling of a number of
distributions related to the fastest growth of the Order Parameter in these
problems. Excellent quality scaling analysis are presented for the two single
peak distributions corresponding to the Order Parameters at the two ends of the
maximal jump, the bimodal distribution constructed by interpolation of these
distributions and for the distribution of the maximal jump in the Order
Parameter.
