About Random Number Generators
A random number generator (RNG) produces a sequence of numbers that cannot be reasonably predicted. RNGs power everything from board games and lotteries to scientific simulations and encryption.
True Random vs. Pseudo-Random
There are two main categories of RNGs:
True random number generators (TRNG)
TRNGs derive randomness from physical phenomena such as atmospheric noise, radioactive decay, or thermal fluctuations. Because they rely on unpredictable physical processes, they are considered truly random. Hardware security modules and services like random.org use TRNGs.
Pseudo-random number generators (PRNG)
PRNGs use a deterministic algorithm to produce sequences of numbers that appear random. Given the same starting seed, a PRNG will always produce the same sequence. Modern PRNGs — including the one in every major web browser — are designed so their output passes rigorous statistical tests for uniformity and independence. For games, raffles, simulations, and everyday picks, a PRNG is indistinguishable from true randomness.
How Math.random() Works
This tool uses JavaScript's built-in Math.random() function. It returns a floating-point number ≥ 0 and < 1. To produce a random integer between a min and max (inclusive), the formula is:
Math.floor(Math.random() × (max − min + 1)) + min
Modern JavaScript engines implement Math.random() using the xorshift128+ algorithm, which has a period of 2128 − 1 and passes the BigCrush statistical test suite. It is fast, uniform, and more than adequate for any non-cryptographic purpose.
Common Uses of Random Numbers
Games and entertainment
Dice rolls, card shuffles, loot drops, procedural level generation — random numbers are the backbone of unpredictable gameplay.
Raffles, giveaways, and lotteries
Assign each entrant a number, set the range, and generate a winner instantly. Using a no-duplicate mode ensures every entrant has a fair, unique draw.
Statistics and sampling
Random sampling is fundamental to surveys, A/B tests, and scientific experiments. Generating a set of unique random indices selects an unbiased sample from a population.
Education
Teachers use random number generators to create quiz questions, randomly assign students to groups, and demonstrate probability concepts in the classroom.