RNG, short for Random Number Generator, refers to a computational or physical process used in computer science, statistics, and gaming to generate numbers that appear random or unpredictable.
In computer science, an RNG is a software algorithm that produces a sequence of numbers that have no pattern or correlation, in order to introduce an element of uncertainty or randomness in various applications. RNGs are commonly used in cryptography, simulation, and procedural content generation where randomness adds complexity and realism.
In statistics, an RNG is a tool used to generate random samples from a given distribution. It allows statisticians to draw conclusions about populations based on a representative subset of data. This helps in performing hypothesis testing and making statistical inferences in various fields like social sciences, economics, and medicine.
In the gaming industry, an RNG is a critical component of ensuring fairness and unpredictability in games of chance. It determines outcomes in games like lotteries, slot machines, and virtual card games. The use of RNGs guarantees that each outcome is independent of previous results, mimicking true randomness and providing a fair gaming experience.
RNGs can be implemented using various methods, such as pseudorandom number generators (PRNGs), hardware-based techniques, or even atmospheric noise. The quality and reliability of an RNG are assessed based on statistical criteria like uniformity, independence, and unpredictability.
