Free Random Number Generator
Uniformly random integers or decimals in any range.
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Inputs
Result
Random number
19
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Short answer
For an integer between min and max inclusive: floor(random × (max − min + 1)) + min. For a decimal: random × (max − min) + min.
What is the Random Number Generator?
A pseudo-random number generator producing uniformly distributed integers or decimals over a range.
How does the Random Number Generator work?
Scale a uniform [0,1) sample by the range width and shift by the minimum. Floor for integers.
Formula
Variables
randUniform [0, 1) — from Math.random()
Explanation
Browsers use PRNGs (typically xorshift128+ or PCG variants) — suitable for games and testing, not cryptography.
Examples
Example 1: 1 to 100, integer
One draw uniformly from {1, 2, …, 100}.
Applications
- Games and simulations
- Test data generation
- Random sampling
Advantages
- Configurable range and count
- Integer or decimal output
Limitations
- Not cryptographically secure — do not use for keys, tokens, or lotteries
Common mistakes
- Using Math.random() for security-sensitive contexts
Tips
- For security, use crypto.getRandomValues() in a dedicated tool
Related concepts
The Random Number Generator sits inside the Math Calculators hub, in the statistics & probability cluster. Describing data and quantifying uncertainty. Understanding the terms below makes the output easier to interpret and easier to compare against neighbouring measures.
Practical use cases and industry applications
Understanding Random Number Generator
A pseudo-random number generator producing uniformly distributed integers or decimals over a range. Within math calculators, random number generator belongs to the statistics & probability cluster, where it shares terminology and assumptions with closely related tools.
Learning how random number generator is calculated
Browsers use PRNGs (typically xorshift128+ or PCG variants) — suitable for games and testing, not cryptography. Working through the variables one at a time — rand — makes the result reproducible by hand and easier to sanity-check.
Using random number generator to make a decision
Games and simulations Test data generation Random sampling Because outputs depend on the assumptions you enter, run more than one scenario before committing to a figure.
How random number generator compares with related measures
distribution, dispersion, significance, sample all describe adjacent aspects of statistics & probability. Comparing this calculator's output against those measures — using the related tools listed on this page — prevents a single metric from being read in isolation.
Frequently asked questions
Is this truly random?
No — pseudo-random. Statistically indistinguishable from random for casual purposes but predictable in principle.
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