Problems encountered so far are completely determined by the models, and will produce the same solutions repeatedly. Some models have terms that occur randomly, and these are called stochastics.

We have already seen one example earlier, that of the price a volatile stock. While the price increases roughly which the underlying price of money, fluctuations were considered to exist on a day-to-day process sampled from a Gaussian process.

Time series analysis is often used to reduce the effect of such fluctuations and reveal the underlying trends, but there are certain systems where the stochastics are paramount. Typical examples are models of queueing systems that might occur in service at banks, or checkouts in supermarkets. I will discuss a particular case of the bank teller later in this section.