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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
- Interpret the two parameter fields according to the selected distribution and validate its mathematical domain.
- Transform independent secure uniform variates with a distribution-specific bounded algorithm.
- 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.