How to perform a Monte Carlo simulation with continuous sampling using discrete quantiles?
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?
Topic monte-carlo distribution probability statistics
Category Data Science