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Principal component analysis (PCA): Unit variance scaling is applied to rows; SVD with imputation is used to calculate the principal components. X and Y axes show principal component 1 and principal component 2 that explain 42.1 and 9.6% of the total variance, respectively. Prediction ellipses are such that with probability 0.95, a new observation from the same group will fall inside the ellipse. N = 130 data points
