ABSTRACT
The term stochastic is derived from the Greek word stochos, which means target,
and connotes an element of chance since a person who is stochastikos is skilful at
aiming. Today, it is used as a modelling term that simply means ‘random’.
Stochastic processes are distinct from deterministic processes since a future state
cannot be completely determined from the previous state and there is a random
component. Many processes in engineering can be considered stochastic, such as
dynamic loads on a building, traffic patterns, rainfall storms, location of mineral
deposits and vibrations of a machine. A stochastic model has the advantage over a
purely deterministic model in that it can model random fluctuations. Probability
distributions that govern these fluctuations form the basis of stochastic models and
for this reason, the distributions discussed in prior chapters play an important role.
However, a critical question becomes: “Which distribution to use?” This chapter
addresses that question.