The R Book, 3rd Edition

19Multivariate Statistics

This class of statistical methods is fundamentally different from many others in the book because there may not be a response variable. Instead of trying to understand variation in a response variable in terms of explanatory variables, in multivariate statistics we look for structure in the data. The problem is that structure is rather easy to find, and all too often it is a feature of that particular data set alone. The real challenge is to find general structure that will apply to other data sets as well. Unfortunately, there is no guaranteed means of detecting pattern, and a great deal of ingenuity has been shown by statisticians in devising means of pattern recognition in multivariate data sets. The main division is between methods that assume a given structure and seek to divide the cases into groups, and methods that seek to discover structure from inspection of the data. The really important point is that we need to know exactly what the question is that we are trying to answer. Do not mistake the opaque for the profound.

incorporates a wide range of multivariate techniques, many of them in extra packages. A good summary can be found at https://cran.r-project.org/web/views/Multivariate.html. The subjects covered in this chapter together are the following:

• visualising data;
• multivariate analysis of variance;
• principal component analysis: analyses ...