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Assume I have registered the duration of 10 tasks and built the table below with using this data:

Duration For how many tasks it happened
4 days 5 task
6 days 2 task
8 days 2 task
10 days 1 task

Looking at this table, one can easily conclude that there's a 50% chance that a task would last 4 days. Therefore, my Monte Carlo simulation will yield "4 days" as the task duration 50% of the time.

However, there's also a possibility that the task would last 5 days, for example, but none of the tasks in my sample dataset took 5 days.

Should my MCS never yield 5 day tasks because it hasn't occurred in the sample data set or is there a way to make these discrete probability quantiles continuous?

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  • $\begingroup$ You could try and find a statistical probability distribution (e.g. a Poisson or geometric distribution) that fits your data well or use something like kernel density estimation to get a distribution you can sample from. $\endgroup$
    – Oxbowerce
    Sep 23 at 12:36

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