Related to the topic of stochastic processes is queueing theory (i.e., the analysis of waiting lines). A common example is the single-server queue in which customer arrivals and service times are random. Figure 1 illustrates the queue, and the curve shows how sensitive the average queue length becomes under high traffic intensity conditions. Mathematical analysis has been essential in understanding queue behavior and quantifying impacts of decisions. Equations have been derived for the queue length, waiting times, and probability of no delay, and other measures. The results have applications in many types of queues, such as customers at a bank or supermarket checkout, orders waiting for production, ships docking at a harbor, users of the internet, and customers served at a restaurant. Examples of decisions in managing queues are how much space to allocate for waiting customers, what lead times to promise for production orders, and what server count to assign to ensure short waiting times.