In case of this queuing model, the Poisson process is followed where the service times that are present are distributed in an exponential manner, and there is specifically a single server.

In this model, arrival rate of customers is taken to be A, whereas a total of S clients can be served at a single place.

Here is a sum, solving which will help students get a better idea of this process.

**Sum 1:** It is taken that a post office has double counters which can handle businesses as letters, registrations and various types of money orders. If it is taken that service time distributions in case of two counters are exponential in nature with the accepted mean service time being 4 minutes for every customer. It can also be taken that customers come down to each of the counters keeping true to the Poisson fashion and the mean arrival rate are taken at 11 on an hourly basis.

**How to find the following:**

- What is the average time to wait in the queue?
- How many idle customers are to be present at the counter?
- What is the probability or the chances that a person has to wait at the counter to be served?

Find out these details, and you will understand the concept in a better manner.

**Links of Previous Main Topic:-**

- Introduction to statistics
- Knowledge of central tendency or location
- Definition of dispersion
- Moments
- Bivariate distribution
- Theorem of total probability addition theorem
- Random variable
- Binomial distribution
- What is sampling
- Estimation
- Statistical hypothesis and related terms
- Analysis of variance introduction
- Definition of stochastic process
- Introduction operations research
- Introduction and mathematical formulation in transportation problems
- Introduction and mathematical formulation
- Queuing theory introduction

**Links of Next Statistics Topics:-**