Monte Carlo Simulation
Risk analysis for profit, cost, or project duration. Sample uncertain inputs thousands of times and read mean, P10/P50/P90, and the full distribution.
Uncertain inputs
Idea
Monte Carlo draws random inputs from specified distributions, evaluates an expression many times, and summarizes the output distribution (mean, stddev, percentiles). It is ideal when formulas are nonlinear or uncertainty is described by ranges rather than closed forms.
Distributions
Uniform — any value between min and max equally likely.
Triangular — min, mode, max (classic for expert project estimates).
Normal — mean μ and stddev σ (symmetric, unbounded — watch negative draws if that is invalid).
Reading percentiles
P10 / P50 / P90 are optimistic / median / pessimistic outcomes under your model. For project duration, P80 or P90 is often used for contingency.
Seeds & trials
A fixed seed makes runs reproducible. More trials smooth the histogram; 2,000–10,000 is usually enough for teaching and screening analysis.
Profit risk
Profit = demand × price − cost with triangular demand, uniform price, normal fixed cost.
Project duration
Sum three triangular activity durations for a simple PERT-style risk forecast.