Set the Arrivals to $9$ per minute and Services to $10$ per minute. You can choose any numbers, but these numbers are used in the subsequent analysis in the videos.

Uncheck the "Random" box to simulate a situation without any variability in either arrivals or service. In other words, each arrival occurs exactly $6\mathrm{.}66(60/9)$ seconds, and each service is completed in $6$ seconds. Hence, you will notice that no queue is built up as the service of each arrival is completed before the next arrival. In other words, the maximum number of persons in the system is one.

Now, check the "Random" box and again observe the graph. You will notice that now the queue builds up and draws down intermittently. This is typical because many arrivals occur in a short duration, but they are not necessarily served at a greater speed. On the other hand, there are periods when arrivals are spaced out so that the queue is served entirely, and the server is idle $($zero in the system on the y$-$axis$).$

Now, try changing the arrival and service rate and repeat the above steps. First, qualitatively observe the queue length behaviour for increasing the ratio of "arrival rate$/$service rate". Second, create a table of $$arrival rate$/$service rate$$ values against "average customers in the system". Plot these values, comment on the nature of the plot and try to articulate an intuitive explanation for it$.$