Pseudo Random Process
A pseudo random refers to a process that generates a sequence of numbers or events that appears random but actually, is not and is determined by a fixed set of rules. Pseudorandom sequences typically exhibit statistical randomness while being generated by an entirely deterministic causal process. Such a process is easier to produce than a genuinely random one and has the benefit that it can be used again and again to produce the same numbers and they are useful for testing and fixing software.
The generation of random numbers has many uses (mostly in Statistics, Random Sampling, and Simulation, Computer Modeling, Markov Chains, and Experimental Design). Before modern computing, researchers requiring random numbers would either generate them through various means like a coin, dice, cards, roulette wheels, card shuffling, etc., or use existing random number tables.
A pseudo-random variable is a variable that is created by a deterministic procedure (often a computer program or subroutine is used) which (generally) takes random bits as input. The pseudo random string will typically be longer than the original random string, but less random (less entropic, in the information-theory sense). This can be useful for randomized algorithms.
Pseudo-random numbers are computer-generated random numbers and they are not truly random because there is an inherent pattern in any sequence of pseudo numbers.
A question arises here why do we use something that is not truly random? The reasons behind the use of pseudo random process are:
- Speed and Efficiency:Â Generating pseudo-random numbers is much faster and more efficient than using true random sources like physical processes.
- Reproducibility:Â Using the same seed, one can reproduce the same sequence of pseudo-random numbers. which is useful for debugging or comparing simulations.
Read more about Random Number Process,
Read more about Pseudo-Random Number Generator
Generate Binomial Random Numbers in R
