The paper deals with a comparison of two different approaches (PERT method and Monte\nCarlo method) for calculation of the probability of a project completion. The PERT method is\ncommonly used in a project management; the Monte Carlo is used less. The base assumption\nof authors can be expressed: The difference between the results obtained by the Monte Carlo\nmethod and PERT method is not significant with increasing number of simulations\n(iterations). For this reason, the hypothesis was formulated: There is no statistically\nsignificant difference between the calculated probabilities, i.e. both approaches are identical\nfrom application�s point of view. The case study describes a model of a project, which is\nshown by a network chart. This chart contains 18 nodes and 18 real activities and 6 fiction�s\nactivities. Each activity is expressed by three time estimates, i.e. pessimistic, most likely and\noptimistic time. The planned date of completion of the project was selected at 200 time units\nand it was calculating the probability of completion of the project by PERT method and\nMonte Carlo method. Time duration of each project activity by the Monte Carlo method is\nsuccessively obtained for 10, 100, 300, 500, 1000, 5000 and 10000 simulations. The\ncalculated probabilities of project completion were compared using statistical hypothesis\ntesting. The hypothesis was rejected for all simulations. It follows that there is difference\nbetween the approaches from application�s point of view.
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