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I will rephrase your question, as to "What relationship does queueing theory and probability therory?" Queueing theory is the mathematical study of waiting lines See: http://en.wikipedia.org/wiki/Queueing_theory Wait times, by their nature, are uncertain but can be represented by probability distributions. From a distribution, I may be able to tell that the chance of waiting more than 5 minutes for service is 10%, or that there is a 95% chance that my complete time in a facility (service time and wait time) is less than 15 minutes. On the other side, queueing theory may determine how often those responsible for service have no customers. The theory has broad applications, ranging from computer networks, telephony systems, delivery of goods and services (such as mail, home repair, etc) to an area and customer service in any location where people might stand in line. Traffic analysis uses queueing theory extensively. The "forward" analyses begins with an assumed probability distribution. Given probability distributions that are thought to describe certain activities (number of customers arriving in a particular time span, time spent with each customer and special events -frequency of events and time spent on special events), the distribution of waiting times can be determined mathematically. Thus, probability theory provides the basis (distribution and mathematical theory) for queueing applications. Today, more complex queueing problems are solved by Monte-Carlo simulation, which after thousands (or hundreds of thousands) of repeated runs, can provide nearly the same accuracy of statistics and distributions as those generated from purely mathematical solution. More broadly, queueing modeling and theoretical solutions are within stochastic process analysis.

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Q: Probability and queuing theory
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