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Determining the number of computers to be purchased in order to achieve an optimum relation between access waiting time and server idleness, is a problem frequently encountered by library supervisors due to rapid development of informatics. In an attempt to solve this problem, in our research we applied a simulation queuing model, as well as an aspiration level model, as its extension. Simulation sets whose expected waiting time in system and idleness do not show statistically significant differences were identified in the paper by the analysis of variance and post hoc comparisons. The initial model was improved by this usage of inferential statistics methods, thus raising the decision-making efficiency in library management.