What is a random number generator?
A random number generator (RNG) is a tool that produces numbers with no predictable pattern within a defined range. Our online RNG generates uniformly distributed random integers — meaning every number in the range has an equal chance of appearing.
How does a random number generator work?
This generator uses the browser's built-in pseudo-random number algorithm. You set a minimum value, a maximum value, and how many numbers you want. The tool then applies the formula: floor(random × (max − min + 1)) + min to produce each integer in the range.
What is the random number generator formula?
For a uniformly distributed random integer between min and max (inclusive), the standard formula is: result = floor(Math.random() × (max − min + 1)) + min. Math.random() returns a float in [0, 1), so multiplying by the range size and flooring gives an even distribution across all integers.
What are some examples of random number generation?
Common examples include rolling a die (min=1, max=6), picking a lottery number (min=1, max=49), generating a PIN code digit (min=0, max=9), or selecting a random item from a list by generating its index. You can also generate multiple numbers at once — for example, 6 numbers in the range 1–49 to simulate a lottery draw.
When is a random number generator useful?
Random number generators are useful for board games and dice rolls, lottery and raffle draws, selecting random winners or participants, making random decisions, creating test data, classroom activities, and statistical sampling exercises. If you want to analyse the numbers you generate, try the Z-score calculator to see how individual values compare to a distribution, or the percentage calculator to express your results as proportions.
Is this random number generator truly random?
This generator uses a pseudo-random algorithm (PRNG), which is random enough for games, decisions, and everyday use but not for cryptographic security. For cryptographically secure random values, use dedicated tools. For all practical purposes — games, raffles, decisions — this generator is perfectly suitable.
Can the same number appear more than once?
Yes — when generating multiple numbers, the same integer can appear more than once. Each number is drawn independently with no memory of previous results, so repetition is a natural property of a truly uniform random distribution. This matches how real dice and lotteries work. If you specifically need a set of unique numbers without repetition — for example, shuffling a playlist or drawing raffle winners — generate numbers one at a time and skip any that have already appeared.
What is the difference between a PRNG and a TRNG?
A pseudo-random number generator (PRNG) uses a deterministic algorithm seeded by system state such as the current time. The output is statistically uniform and unpredictable in practice, but technically reproducible if the seed is known. A true random number generator (TRNG) derives randomness from physical phenomena — atmospheric noise, radioactive decay, or electrical fluctuations — and is genuinely non-deterministic. TRNGs are slower and reserved for cryptographic key generation. For games, raffles, and everyday decisions, a PRNG is entirely appropriate and indistinguishable from true randomness.