Generation of pseudorandom numbers
Related Experiment Video
Updated: Oct 8, 2026

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
Published on: March 18, 2019
Abstract:
Computational studies requiring the generation of pseudorandom numbers are becoming increasingly common. These include Monte Carlo methodologies and studies which require the addition of "random" noise to more structured data. Although well-established random number generators exist, many of these are not suitable for implementation on micro- or minicomputer systems. An algorithm for an additive generator that can be used on any computer system is described. The performance of this algorithm as implemented on a microcomputer system is discussed. Extensive testing of the statistical behavior of the resulting number sequence was performed. The algorithm appears to be an appropriate one for a variety of applications.
More Related Videos
08:34Generation of In-Frame Gene Deletion Mutants in Pseudomonas aeruginosa and Testing for Virulence Attenuation in a Simple Mouse Model of Infection
Published on: January 8, 2020
09:25Rapid, Seamless Generation of Recombinant Poxviruses using Host Range and Visual Selection
Published on: May 24, 2020
Related Concept Videos
Random Sampling Method
Random Variables
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Random Error
Propagation of Uncertainty from Random Error
Wald-Wolfowitz Runs Test II
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
Generation Time