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In probability and statistics, the PERT distributions are a family of continuous probability distributions defined by the minimum (a), most likely (b) and maximum (c) values that a variable can take. It is a transformation of the four-parameter beta distribution with an additional assumption that its expected value is
PERT network chart for a seven-month project with five milestones (10 through 50) and six activities (A through F). The program evaluation and review technique ( PERT ) is a statistical tool used in project management , which was designed to analyze and represent the tasks involved in completing a given project .
A discrete power-law distribution, the most famous example of which is the description of the frequency of words in the English language. The Zipf–Mandelbrot law is a discrete power law distribution which is a generalization of the Zipf distribution. Conway–Maxwell–Poisson distribution Poisson distribution Skellam distribution
For example, a triangular distribution might be used, depending on the application. In three-point estimation, three figures are produced initially for every distribution that is required, based on prior experience or best-guesses: a = the best-case estimate; m = the most likely estimate; b = the worst-case estimate
It's much less popular than PERT (Program Evaluation and Review Technique) or CPM (Critical Path Method) however, it allows some of those methods limitations to be addressed. The main limitations of PERT or CPM that might be addressed by GERT are: there are no alternative paths - all activities have to be performed
An example of this type of directed acyclic graph are those encountered in the causal set approach to quantum gravity though in this case the graphs considered are transitively complete. In the version history example below, each version of the software is associated with a unique time, typically the time the version was saved, committed or ...
The example contains PERT calculations which have nothing whatsoever to do with Gantt and were not developed until around 40 years after his death. May I refer the author and others interested in the subject to two excellent papers from Patrick Weaver; ‘Henry L Gantt, 1861 – 1919.
In such discussions it is important to be aware of the problem of the gambler's fallacy, which states that a single observation of a rare event does not contradict that the event is in fact rare. It is the observation of a plurality of purportedly rare events that increasingly undermines the hypothesis that they are rare, i.e. the validity of ...