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Probability Playground overview

Probability Playground lets you answer back-of-the-envelope questions by writing a simple model and instantly seeing the output distribution.

What it does​

You write a model in a mini-language — a few lines declaring random variables and derived calculations — and the playground runs 1,000 simulation iterations, then shows a histogram of the output.

Who this is for​

  • Data scientists and analysts who need quick distribution checks without setting up a full Monte Carlo environment.
  • Product managers evaluating TAM, pricing scenarios, or feature adoption ranges.
  • Engineers estimating latency budgets, failure rates, or capacity planning numbers.
  • Students and educators exploring probability concepts interactively.
tip

No account required. Authenticated users can save and reload models.

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

Layout​

The page has two panes:

Editor (left):

  • Text area for your model
  • Run button
  • Save button (authenticated users)
  • Error messages below the editor

Visualization (right):

  • Histogram of the last declared variable (or any variable you select)
  • Draggable Pr(x < X) line
  • Summary statistics

Quick start​

  1. Write a model — declare one or more random variables and a derived calculation in the editor (left pane). For example:

    revenue ~ uniform(1e6, 5e6); costs ~ normal(500000, 100000); profit = revenue - costs;

  2. Click Run — the playground executes 1,000 simulation iterations and displays a histogram of your output variable in the right pane.

  3. Read the histogram — examine the shape, spread, and central tendency of the distribution.

  4. Drag the Pr(x < X) line — click and drag the vertical line on the histogram to see the probability that the output falls below a given value.

  5. Save your model (authenticated users) — click Save to keep your model for later sessions.

Next steps​