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Integers, Decimals, Dice, Lottery & PIN Picks
Enter a minimum, maximum, and count to generate random integers or decimals within any range. Options include unique numbers, sorted output, and presets for dice rolls, lottery picks, and PINs. A seed makes results reproducible.
The default mode uses JavaScript's Math.random(), which returns a pseudo-random float uniformly distributed between 0 (inclusive) and 1 (exclusive). For integers, the formula is Math.floor(Math.random() × (max − min + 1)) + min. Both bounds are inclusive, so min and max can both appear in results.
For decimal output, the scaled value is rounded to the chosen decimal places using standard rounding (halfway rounds away from zero). Setting decimal places to 0 is equivalent to integer mode. The underlying PRNG is not cryptographically secure — it is well-suited for games, simulations, and statistics, but not for cryptographic keys or security tokens.
Enabling unique output ensures no value appears twice. For integer ranges up to 10,000 values wide, a Fisher-Yates shuffle is performed on the complete range array and the first N elements are selected. For larger ranges, rejection sampling draws one number at a time and discards duplicates. For decimal output, the formatted string (e.g. "3.14") is the uniqueness key. If the count exceeds available unique values, an error is returned.
A seed initialises a deterministic sequence using the mulberry32 algorithm. The same seed, range, and count always produce identical output — useful for classroom demonstrations, software testing, or sharing a specific random sequence. Changing any digit of the seed produces a completely different sequence. The seeded mode is not cryptographically secure.
FAQ
Short answers for readers and answer engines.
They are pseudo-random. JavaScript's Math.random() passes statistical tests but is not cryptographically secure. It is suitable for games, statistics, decisions, and simulations — not for cryptographic keys or security tokens.
Yes. Set the minimum to a negative value — for example, −100 to 100 — and the generator covers the full range. Both bounds are inclusive.
A seed initialises a deterministic sequence. The same seed, range, and count always produce identical output — useful for reproducible examples, testing, or sharing a specific set of numbers.
For integer ranges ≤ 10,000 values, a Fisher-Yates shuffle is applied and the first N elements are taken. For larger ranges, rejection sampling discards duplicates. If count exceeds available unique values, an error is shown.
Up to 10,000 numbers per run. Integer generation completes quickly at any count. Unique decimals with high precision may take slightly longer due to rejection sampling.
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