# Intuitive overview of principal components analysis (PCA)

I found an excellent and short introductory tutorial pdf on principal components analysis (PCA). It provides a good overview of the following concepts in a particularly intuitive manner:

- Mean Average
- Standard Deviation
- Variance
- Co-Variance
- Matrix transformations
- Eigenvectors & EigenValues
- Principal Component Analysis

Unfortunately I found the eigenvectors bit a bit heavy going. Luckily the wikipedia page for eigenvectors has a fantastic illustration on the right that gave me an instant feel of what was happening.