The article explores different ways to estimate a parameter in the Erlang distribution using Bayesian methods. It looks at three types of prior distributions and compares their effectiveness. The researchers also use maximum likelihood to estimate another parameter. Through simulations, they calculate the mean and mean square error of the parameter estimates. Finally, they provide point and interval estimates for the parameter under different scenarios.