Figure 3. Schematic of principal component analysis (PCA) in geometric space. Two dimensional shapes are assigned polar coordinates (x,y) so that many, disparate shapes can be statistically compared on one graph. From this graph, the principal components of variation can be determined by which lines best identify the largest variance of the data (red lines).