Random Number Generator

Generate random numbers with customizable ranges and options. Perfect for games, simulations, statistical sampling, and decision making.

Features and Options

Custom Range: Define minimum and maximum values

Multiple Numbers: Generate sets of random numbers

Uniqueness Control: Allow or prevent duplicates

Sorting Options: Order results as needed

Understanding Randomness

Random number generation underpins simulations, sampling, cryptography, gaming, lotteries, and A/B testing. In a browser, numbers are produced by a pseudo‑random algorithm seeded by implementation‑specific entropy sources. While sufficient for most non‑security use cases, browser randomness should not be relied upon for high‑stakes cryptography or regulated drawings without additional safeguards.

Common Use Cases

  • Sampling: Select k items uniformly from a list without replacement
  • Simulations: Monte Carlo methods for probability and risk analysis
  • Games: Dice, loot tables, map seeds, turn order, procedural content
  • Education: Probability experiments and classroom activities
  • A/B Testing: Traffic allocation with fixed or weighted ratios

Avoiding Bias

  • Uniform Ranges: Map to [min, max] inclusively using integer math to avoid floating bias
  • No Replacement: Track a set of used values; retry on collision (as this tool does)
  • Sorting After Draw: Draw first, then sort results if you need ordered output
  • Validation: Ensure max − min + 1 ≥ count when duplicates are disallowed

Seeding and Reproducibility

This tool uses the browser’s built‑in randomness and does not expose a user‑seed option. For reproducible sequences (e.g., in research), use a seeded PRNG (such as Mulberry32 or xorshift) with a fixed seed, and record the seed alongside results so trials can be replicated exactly.

Security Considerations

Do not use front‑end random numbers for cryptographic keys, password generation for sensitive accounts, or regulated drawings. For high‑integrity scenarios, generate numbers on a server using a CSPRNG and, if necessary, publish signed transcripts or hash commitments for auditability.

Key points

  • Numbers are pseudo-random from the browser and fit typical non-security use cases.
  • Range is inclusive: minimum and maximum can appear in results.
  • Disable duplicates to sample without replacement.
  • Each run generates a new sample; enable sorting to compare runs more easily.