First, select units of time you want to analyze.

It can be any time units depends on the specific context and requirements.

Example: the time units is 1 hour and average customers per hour is 10 customers per hour, then the arrival rate (λ) is 10 customers/hour.

Select a queueing model base on the data and context.

`M/M/c`

If you know average number of customers that be served per server.

Example: A cashier can serve 20 customers per hour on average, then the service rate (μ) is 20 customers/hour.

`M/M/c/K`

Similar to `M/M/c`

but if the system have limit maximum number of customers.

Example: A cafe only have 10 tables for customers, then K is 10.

`M/D/1`

If the service times are deterministic (constant). It can be estimate by Little’s law.

Example: A cashier will take 3 minues per service on average, then in 1 hour the service rate (μ) is 60/3 = 20 customers/hour.

`c`

mean number of servers, if the number is dynamic recommend to use 1 or use simulation techniques instead.