In Multivariate Statistics (I) with R, our aim is to learn some statistical analysis and visualization techniques : Principal Component Analysis (PCA), Factor Analysis (FA), Cluster Analysis (CA) for multivariate data which are measuring the various social present situations by many variables and observations. Recently, multivariate statistics provides some absolute and essential techniques for Big data(Unstructured data, Structured data) and data mining. In this lecture, we have a good chance to raise our understanding multivariate data and to study some powerful analysis techniques. With R practices, we will be experienced in results' interpretations of data analysis.
Next semester, Multivariate Statistics (II) with R will give some statistical analysis and visualization techniques : Discriminant Analysis (DA), Multidimensional Scaling (MDS), Correspondence Analysis (CRA) and Machine Learnings(SVM, ANN, DNN).