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.