Lecture
Principal Components: Properties & Applications
Description
This lecture covers the definition and properties of principal components, including population and sample principal components, covariance matrix, and eigenvectors. It also discusses the correlation structure, choice of components, and graphical representations. The instructor explains the proportion of variance explained by each component and provides insights on testing hypotheses about principal components.
Official source
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