Random Number Generator

Generate random integers and decimals with advanced options

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Random Number Generator

This version of the generator creates a random integer. It can deal with very large integers up to a few thousand digits.

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🎲 Simple Random ⚙ī¸ Comprehensive Version

🎲 Simple Random Number Generator

📊 Random Number Result

Your random number is:
42

Note: This generator creates random integers within your specified range. Each generation is independent and has equal probability for all numbers in the range.

⚙ī¸ Comprehensive Random Number Generator

This version of the generator can create one or many random integers or decimals. For decimal numbers, you can specify precision up to 999 digits. High-precision calculations (>15 digits) are automatically handled by our backend for maximum accuracy.

numbers
Type of result to generate?
decimal places (max 999)
High precision (>15 digits) automatically uses backend processing

Results

Click "Generate" to create random numbers

📚 Understanding Random Numbers

What is a Random Number?

A random number is a number chosen from a pool of limited or unlimited numbers that has no discernible pattern for prediction. The pool of numbers is almost always independent from each other.

Random Number Generators

A random number generator is a device that can generate one or many random numbers within a defined scope. Random number generators can be hardware based or pseudo-random number generators.

Pseudo-Random Numbers

A pseudo-random number generator is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. Computer based random number generators are almost always pseudo-random.

Random Number Applications

Random numbers have numerous applications in various fields including statistics, computer science, gaming, cryptography, and scientific simulations. The random number generators above assume that the numbers generated are independent of each other, and will be evenly spread across the whole range of possible values.

Important Notes

  • Independence: Each generated number is independent of previous results
  • Distribution: Numbers are evenly distributed across the specified range
  • Sufficient for most applications: These generators work well for most non-cryptographic purposes
  • Not cryptographically secure: Should not be used for security-critical applications
  • True randomness: True random numbers require physical phenomena like atmospheric noise