A Better Approach to Generating Random Numbers

  • Nachandiya Nathan Lecturer, Department of Computer Science, Adamawa State University, Mubi, Nigeria.
  • Samaila Andrew Mamza Student, Department of Computer Science, Adamawa State University, Mubi, Nigeria.
Keywords: Random Number Generator, Pseudocode Random Number, True Random Number, Mid Square Method, Linear Congruential Method, Fibonacci Series, seed value


The term random number has been used by many scholars to explain the behaviour of a stochastic system. Many of such scholars with statistical or mathematical background view it as an organized set of numbers produced by a function in a numerical way in which the next number to be produced is unknown or unpredictable. This paper produced software that generates a sequence of random number and also compared the algorithm with the commonly used method of random number generator. The three most common methods selected were the Mid Square method, Fibonacci method and Linear Congruential Generator Method (LCG). The result shows that the LCG provides a more acceptable result in terms of speed, long cycle, uniformity and independence Applications of this random numbers can be seen in Monte Carlo simulations, simulation or modelling, password generation, cryptography and online games.


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How to Cite
Nachandiya Nathan, and Samaila Andrew Mamza. 2019. “A Better Approach to Generating Random Numbers”. Mathematical Journal of Interdisciplinary Sciences 8 (1), 29-35. https://doi.org/10.15415/mjis.2019.81005.