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Principal Component Analysis — Theory and Computation

A comprehensive PCA tutorial covering eigenvalue decomposition of covariance and correlation matrices, proportion of variance explained, scree plots, principal component scores, and dimensionality reduction applications in multivariate analysis and data science.
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More about this material

Material Type:
Tutorial
Date Added to MERLOT:
March 1, 2026
Date Modified in MERLOT:
March 1, 2026
Author:
Unknown (Know the author?)
Submitter:
Kevin hqy
Primary Audience:
College Upper Division
Technical Format:
Website
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
Unknown
Source Code Available:
Unknown
Creative Commons:
Unknown

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