<Table> <Tr> <Td> </Td> <Td> This article needs additional citations for verification . Please help improve this article by adding citations to reliable sources . Unsourced material may be challenged and removed . (June 2009) (Learn how and when to remove this template message) </Td> </Tr> </Table> <Tr> <Td> </Td> <Td> This article needs additional citations for verification . Please help improve this article by adding citations to reliable sources . Unsourced material may be challenged and removed . (June 2009) (Learn how and when to remove this template message) </Td> </Tr> <P> Random number generation is the generation of a sequence of numbers or symbols that cannot be reasonably predicted better than by a random chance, usually through a random - number generator (RNG). </P> <P> Various applications of randomness have led to the development of several different methods for generating random data, of which some have existed since ancient times, among whose ranks are well - known "classic" examples, including the rolling of dice, coin flipping, the shuffling of playing cards, the use of yarrow stalks (for divination) in the I Ching, as well as countless other techniques . Because of the mechanical nature of these techniques, generating large numbers of sufficiently random numbers (important in statistics) required a lot of work and / or time . Thus, results would sometimes be collected and distributed as random number tables . Nowadays, after the advent of computational random - number generators, a growing number of government - run lotteries and lottery games have started using RNGs instead of more traditional drawing methods . RNGs are also used to determine the outcomes of modern slot machines . </P>

Random numbers are commonly used in which type of program