Multivariate Approach to Partial Correlation Analysis
Science Journal of Applied Mathematics and Statistics
Volume 3, Issue 3, June 2015, Pages: 165-170
Received: May 13, 2015; Accepted: May 29, 2015; Published: Jun. 11, 2015
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Author
Onyeneke Casmir Chidiebere, Mathematics and Statistics Department, University of Calabar, Calabar, Nigeria
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Abstract
Multivariate approach to generate variance covariance and partial correlation coefficients of one or more independent variables has been the concern of advanced statisticians and users of statistical tools. This work tackled the problem by keeping one or some variables constant and partitioned the variance covariance matrices to find multivariate partial correlations. Due to the challenges that faced the analysis and computation of complex variables, this research used matrix to ascertain the level of relationship that exist among these variables and obtained correlation coefficients from variance covariance matrices. It was proved that partial correlation coefficients are diagonal matrices that are normally distributed. (Work count = 101).
Keywords
Multivariate, Correlation, Partial, Normality, Coefficients, Variables, Matrices
To cite this article
Onyeneke Casmir Chidiebere, Multivariate Approach to Partial Correlation Analysis, Science Journal of Applied Mathematics and Statistics. Vol. 3, No. 3, 2015, pp. 165-170. doi: 10.11648/j.sjams.20150303.20
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