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### Simulating Multivariate Random Normal Data using Statistical Computing Platform R

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Simulating Multivariate Random Normal Data using Statistical Computing Platform R

Mehmet Turegun

https://doi.org/10.31142/ijtsrd23987

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, pp.1126-1132, URL: https://www.ijtsrd.com/papers/ijtsrd23987.pdf

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).

Cholesky decomposition, Eigen decomposition, simulation of multivariate random normal data, variance-covariance matrix, R

IJTSRD23987
Volume-3 | Issue-4, June 2019
1126-1132
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470