Random Number Generator: Simple Tool for Statistical Sampling
A random number generator is a software program or hardware device that generates a sequence of numbers or symbols that lack any pattern, i.e. they appear to be randomly generated. Random number generators have applications in gambling, statistical sampling, computer simulation, cryptography, and other fields.
What is Random Number Generator?
A random number generator (RNG) is a computational or physical device designed to generate a sequence of numbers or symbols that lack any pattern and appear to be randomly generated. RNGs have a variety of uses:
- In gambling, RNGs are used for games like slots, roulette, keno, and bingo to ensure unpredictable and unbiased outcomes.
- In statistics, RNGs are used to select random samples for statistical analysis and simulations.
- In computer programming, RNGs are used to initialize variables, simulate unpredictable behavior, and encrypt data.
- In cryptography, RNGs generate cryptographic keys to help secure sensitive data.
There are two main types of RNGs:
- Pseudorandom number generators (PRNGs) - Algorithmic software programs that generate randomness using mathematical formulas. They start with an initial 'seed' value and produce sequences that are not truly random but appear random enough for some purposes.
- True random number generators (TRNGs) - Hardware devices that generate randomness from physical processes like radioactive decay, thermal noise, ring oscillator jitter, or atmospheric fluctuations. They have higher entropy and unpredictability than PRNGs.
A good RNG will pass various statistical tests for randomness. High-quality randomness is essential for many applications like simulation and cryptography to help model reality or generate secure keys.