Random Number Generator

Generate random numbers within any range. Support for multiple numbers, unique values, and sorting.

Result

Fill in the fields above, then press Generate.

A random number generator produces uniformly distributed pseudo-random integers within a specified range, with options for uniqueness and sorting.

Enter a minimum and maximum value to define the range of numbers to generate. Set how many numbers you want (1 to 1,000). Choose whether duplicate numbers are allowed and whether you want the results sorted. Click Generate to produce your random numbers instantly. Results can be copied for use in other applications.

Examples

Lottery-style draw

Set min to 1, max to 49, count to 6, and duplicates to No. This generates 6 unique numbers between 1 and 49, similar to a lottery draw.

Dice roll simulation

Set min to 1, max to 6, and count to 2 with duplicates allowed. This simulates rolling two standard six-sided dice.

Random team assignment

To randomly assign 30 students to 5 teams, generate 30 numbers from 1 to 5 with duplicates allowed. Each number represents a team.

Frequently Asked Questions

Are the numbers truly random?
The numbers are pseudo-random, generated by the JavaScript Math.random() function. They are suitable for games, simulations, and general-purpose randomization, but should not be used for cryptographic security or high-stakes gambling.
Why can't I generate more unique numbers than the range allows?
If duplicates are not allowed, the count cannot exceed the total numbers in the range. For example, with a range of 1-10 you can generate at most 10 unique numbers because there are only 10 distinct integers in that range.
Can I generate decimal numbers?
This generator produces integers only. For decimal random numbers, you can divide the results by a power of 10 (e.g., dividing by 100 gives two decimal places).
Is the distribution uniform?
Yes. Each integer in the specified range has an equal probability of being selected, resulting in a uniform distribution.

Related Information

Random number generation is used extensively in statistics for sampling, in computer science for algorithms like Monte Carlo simulations, in gaming for fair outcomes, and in education for generating practice problems. Pseudo-random number generators (PRNGs) use deterministic algorithms seeded by an initial value, while true random number generators (TRNGs) derive randomness from physical phenomena.

Related Calculators
Probability Calculator
Dice Roller Calculator
Permutation & Combination Calculator
Number Sequence Calculator

Quick Tips

  • •Double-check your inputs — small errors lead to incorrect results.
  • •Disable duplicates for lottery-style draws where each number must be unique.
  • •Use the sort option to make large sets of generated numbers easier to scan.