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Probability Distribution Sampler

Draw bounded samples from common discrete and continuous probability models with declared parameters. The complete workflow runs locally in this browser, with visible controls and a result you can inspect before copying or downloading.

LOCAL WORKBENCH

Generate a result

No upload · no account · no URL storage

Ready. Entries and results stay in this browser tab.

Choose your settings, then select Generate.

How it works

  1. Interpret the two parameter fields according to the selected distribution and validate its mathematical domain.
  2. Transform independent secure uniform variates with a distribution-specific bounded algorithm.
  3. Return the samples plus observed count, mean, and range without implying a goodness-of-fit result.

Worked example

Normal with mean 0 and standard deviation 1 uses those two parameters; binomial uses trial count and success probability instead.

Limits and interpretation

  • Runs are capped at 10,000 samples and algorithms impose bounded retry or tail limits.
  • Displayed rounding can make distinct continuous draws look equal.
  • This educational sampler is not a financial, medical, safety, or cryptographic simulation engine.

Privacy

Your inputs and generated results stay in this browser. This tool does not put them in a URL, analytics event, server log, or external request.

Frequently asked questions

How does Probability Distribution Sampler make its random choices?
Each model starts from Web Crypto uniform variates; the result describes algorithmic pseudo-sampling from the selected mathematical distribution.
Does Probability Distribution Sampler upload my inputs or results?
No. Values stay in the current browser tab and are not placed in the URL, analytics, storage, or network requests.
When should I use Probability Distribution Sampler?
Use it to explore model shapes, create bounded fixtures, or support lessons where distribution and parameters are stated explicitly.

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