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Core concepts

  • Distribution — a way of describing a value that isn't fixed. Instead of saying "delivery takes 5 days", you'd say "delivery usually takes 4–7 days, most often around 5". A distribution is a shape for that uncertainty; see Distribution parameters for the full list supported here.
  • Random variable — a value drawn from a probability distribution each iteration. You declare it with ~ (tilde) followed by a distribution name and parameters.
  • Derived variable — a value computed from other variables using arithmetic. You declare it with = followed by an expression.
  • Output variable — the last variable you declared in your model. The histogram shows its distribution by default. You can also select a different variable from the dropdown.

Example use cases​

  • TAM/SAM/SOM estimate:

    tam ~ uniform(1e9, 5e9); sam_fraction ~ uniform(0.01, 0.05); sam = tam * sam_fraction;

  • Project NPV: model revenue and cost as distributions, then compute NPV as a derived variable

  • Probability of hitting a target: read off Pr(x < X) from the histogram