Multivariate Data Analysis Using R Software

Multivariate analysis is branch of statistics designed to reduce the complexity of high dimensional data by creating a low- dimensional representation of the data without ignoring the relationships among individual taxa. R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It is integrated collection of intermediate tools; graphical facilities and display either directly at the computer or on hardcopy make it vital. R is very much a vehicle for newly developing methods of interactive multivariate data analysis. It has developed rapidly, and has been extended by a large collection of packages. R is adventitious Over SAS and SPSS because the data input management system, statistical and graphical procedure, and output management system and matrix language. The application of R in matrix, analysis of variance (ANOVA), regression analysis, cluster analysis and ordination methods such as Principal Components Analysis (PCA), Principal Co-ordinates Analysis (PCoA), Correspondence Analysis, Detrended Correspondence Analysis and Multi-Dimensional Scaling (MDS) for different disciplines is described in this book.

He graduated BSC degree in plant Science at Alemaya University and MSC in Environmental Science at Addis Ababa University. He has experiences on development works, research and teaching. Now he is instructor at Wollo University while attending his doctorate degree (PhD) in Addis Ababa University of Ethiopia.