Principal Component Analysis (PCA) – Practice Quiz

Build a working understanding of principal component analysis through sensor, laboratory and business examples. Practice spectral decomposition, component scores, explained variance, scree plots, scaling choices and reconstruction, then examine instability, leakage and prediction pitfalls. Prerequisites: covariance matrices, eigenvectors, linear algebra and multivariate distributions. Includes single-select and multiselect problems with worked solutions and distractor explanations.

Reading: Statistical reference 1.