Author(s)

Pirooz Mohazzabi, Michael J. Connolly

Department of Mathematics and Physics, University of Wisconsin-Parkside, Kenosha, WI, USA.

A new algorithm is suggested based on the central limit theorem for generating pseudo-random numbers with a specified normal or Gaussian probability density function. The suggested algorithm is very simple but highly accurate, with an efficiency that falls between those of the Box-Muller and von Neumann rejection methods.

Random Numbers, Central Limit Theorem, Normal Distribution, Gaussian Distribution

Mohazzabi, P. and Connolly, M. (2019) An Algorithm for Generating Random Numbers with Normal Distribution. Journal of Applied Mathematics and Physics, 7, 2712-2722. doi: 10.4236/jamp.2019.711185.