![On Bartlett's sphericity test for correlation](https://blogs.sas.com/content/iml/files/2017/01/ProgrammingTips-2.png)
When you have many correlated variables, principal component analysis (PCA) is a classical technique to reduce the dimensionality of the problem. The PCA finds a smaller dimensional linear subspace that explains most of the variability in the data. There are many statistical tools that help you decide how many principal