  Although first-order rate constants are basic ingredients of physical
chemistry, biochemistry and systems modeling, their innermost nature is derived
from complex physical chemistry mechanisms. The present study suggests that
equivalent conclusions can be more straightly obtained from simple statistics.
The different facets of kinetic constants are first classified and clarified
with respect to time and energy and the equivalences between traditional flux
rate and modern probabilistic modeling are summarized. Then, a naive but
rigorous approach is proposed to concretely perceive how the Arrhenius law
naturally emerges from the geometric distribution. It appears that (1) the
distribution in time of chemical events as well as (2) their mean frequency,
are both dictated by randomness only and as such, are accurately described by
time-based and spatial exponential processes respectively.
