How does a random number generator work?

Computer RNGs use algorithms (pseudorandom) seeded with unpredictable values like system time or hardware noise. Cryptographic RNGs use true randomness from physical sources. Our generator uses the Web Crypto API for cryptographically secure random numbers.

Are computer-generated random numbers truly random?

Most are pseudorandom—deterministic algorithms that appear random. Given the same seed, they produce identical sequences. Cryptographically secure PRNGs (like Web Crypto API) are unpredictable for practical purposes. True randomness requires physical sources like radioactive decay or atmospheric noise.

What is the range of random numbers I can generate?

Our tool generates integers within any range you specify, including negative numbers. For lottery numbers (1-49), picking teams (1-N), or simulations. JavaScript safely handles integers up to 9,007,199,254,740,991.

How do I generate random numbers without repeats?

For unique random numbers (like lottery draws), either shuffle a list and take the first N items, or generate numbers and track which have been used. Our tool can generate multiple unique numbers in a range without duplicates.

What is the difference between uniform and normal distribution?

Uniform distribution: each number has equal probability (dice rolls, lottery). Normal (Gaussian) distribution: numbers cluster around a mean with bell curve shape (heights, test scores). Most simple RNGs produce uniform distribution.

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Random Number Generator

Random number generators produce unpredictable numbers within a specified range. Cryptographically secure RNGs use entropy sources for true randomness. Probability is uniform: each number in range has equal chance of being selected.

Generate cryptographically secure random numbers, roll dice, flip coins, and pick lottery numbers. Supports integer or decimal mode, duplicates toggle, sorting, dice roller (d4–d100), coin flipper (1–100 coins), and lottery picker with presets. History of last 20 generations.

Minimum

Maximum

How Many

Allow duplicatesSort resultsDecimals

About This Generator

Uses crypto.getRandomValues() for cryptographically secure randomness
Generate integers or decimals with configurable precision
Dice roller supports d4, d6, d8, d10, d12, d20, and d100
Coin flipper shows heads/tails count with visual chips
Lottery picker draws unique numbers, sorted automatically
Press Enter to quickly re-generate

How to Use

Enter your value in the input field
Click the Calculate/Convert button
Copy the result to your clipboard

Frequently Asked Questions

How does a random number generator work?: Computer RNGs use algorithms (pseudorandom) seeded with unpredictable values like system time or hardware noise. Cryptographic RNGs use true randomness from physical sources. Our generator uses the Web Crypto API for cryptographically secure random numbers.
Are computer-generated random numbers truly random?: Most are pseudorandom—deterministic algorithms that appear random. Given the same seed, they produce identical sequences. Cryptographically secure PRNGs (like Web Crypto API) are unpredictable for practical purposes. True randomness requires physical sources like radioactive decay or atmospheric noise.
What is the range of random numbers I can generate?: Our tool generates integers within any range you specify, including negative numbers. For lottery numbers (1-49), picking teams (1-N), or simulations. JavaScript safely handles integers up to 9,007,199,254,740,991.
How do I generate random numbers without repeats?: For unique random numbers (like lottery draws), either shuffle a list and take the first N items, or generate numbers and track which have been used. Our tool can generate multiple unique numbers in a range without duplicates.
What is the difference between uniform and normal distribution?: Uniform distribution: each number has equal probability (dice rolls, lottery). Normal (Gaussian) distribution: numbers cluster around a mean with bell curve shape (heights, test scores). Most simple RNGs produce uniform distribution.