Multivariate Data Analysis by Programming

Multivariate Data Analysis involves analysis of more than two related variables. This tutorial shows multivariate data analysis using R program. R is used for data analysis widely. I will show analysis of principal component analysis, Factor Analysis, Kmeans clustering, Hierarchical Clustering, eigen vector analysis. I have shown installation of R program here. I read csv data into the console. Principal component analysis contains the program and screeplot to explain the components. Factor analysis has been performed using maximum likelihood estimation technique. Canonical correlation shows the correlation between partitioned data here. Hierarchical cluster model has been estimated by both complete and average methods. Dendogram has been made both for complete and average method. Kmeans cluster has been analyzed here with center information. R program has been used using manual from the systems. There are built in functions into the system. Princomp, hclust, screeplot, plot, xlab, main, kmeans, factanal, cancor functions have been successfully used here. To read data read.csv and read.table both method have been shown here. The analysis could help for analyzing data, research and study. R is used for versatile research and project works to solve practical problems. All programs have been stored and attached for your learning along with the data file.