In the field of High Energy Particle physics, Multivariate Analysis (MVA) has become synonomous with machine learning, or even as far as to be confused with multivariate supervised classification. The field instead is a branch of mathematics with great and far reaching applications in both of these fields and throughout statistics in general.
These lecture notes are formed of several chapters loosely based on the textbook, Methods of Multivariate Analysis by A.C. Rencher. The chapters currently covered are:
- Matrix Algebra Pt.1
- Matrix Algebra Pt.2
- Describing Data
- Multivariate Gaussians
- Binned Likelihood Fits
- Minimizing Functions
- Statistical Tests
- Discriminant Analysis
- Classification Analysis
- Multivariate Regression