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.