Abstract :
Many faculty members, as well as students, in the area of educational research methodology, sometimes have a need for generating data to use for simulation and computation purposes, demonstration of multivariate analysis techniques, or construction of student projects or assignments. As a great teaching tool, using simulated data helps us understand the intricacies of statistical concepts and techniques. The process of generating multivariate normal data is a nontrivial process and practical guides without dense mathematics are limited in the literature Nissen and Saft, 2014 . Hence, the purpose of this paper is to offer researchers a practical guide for and a quick access to generating multivariate random data with a given mean and variance covariance structure. A detailed outline of simulating multivariate normal data with a given mean and variance covariance matrix using Eigen or spectral and Cholesky decompositions is presented and implemented in statistical computing platform R version 3.4.4 R Core Team, 2018 . Mehmet Turegun "Simulating Multivariate Random Normal Data using Statistical Computing Platform R" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23987.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/23987/simulating-multivariate-random-normal-data-using-statistical-computing-platform-r/mehmet-turegun
Keyword :
Cholesky decomposition, Eigen decomposition, simulation of multivariate random normal data, variance-covariance matrix, R