how to respond to my peer;s statement - To calculate these queuing metrics, we can use the M/M/1 queuing model, where arrivals follow a Poisson distribution and service times follow an exponential distribution (Borchia, 2024). First, we need to calculate the arrival and service rates. Arrival rate is the average number of arrivals per time period and service rate is the average number of customers served per time period (Beasley, 2019). The arrival rate is given (20 customers per hour) and the service time is 2 minutes per customer, service rate is 60/2 = 30 customers per hour. Arrival rate() = 20/60 = 1/3 Service rate () = Traffic intensity or utilization (p) = 20/30 = 67% As the customers are served faster than they arrive, it could be stated that the system is in a stable state and can handle the incoming load effectively without getting overwhelmed. The utilization of 67% indicates that the system is fairly busy. A utilization of 100% would mean that the system is fully utilized, while a utilization of less than 100% suggests that there are idle times. Since the arrival rate is less than the service rate, the system is not operating