As a random number, the result of special random experiments is called.
Random numbers are required for different statistical methods, for example, in selecting a random sample from a population, in the distribution of animals in different experimental groups ( randomization), at the Monte Carlo simulation and Others
For the generation of random numbers, there are various methods. These are called random number generators. A decisive criterion for random numbers is whether the result of the generation to be independent of previous results can be viewed or not.
True random numbers are generated by physical phenomena: coin toss, dice, roulette, noise electronic components, radioactive decay processes or quantum effects. These methods are called physical random number generators, but are time- consuming or technically right.
In the real-world application is often sufficient, a sequence of pseudo-random numbers, which are seemingly random numbers, which are generated according to a fixed, reproducible process. So they are not random, since they can be predicted, but have similar statistical properties ( uniform frequency distribution, low correlation ) as true random number sequences. Such processes are called pseudo-random number generators.
For other purposes, for example in the generation of cryptographic keys, while true random numbers are needed.