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ERIC Number: EJ1060951
Record Type: Journal
Publication Date: 2015
Pages: 21
Abstractor: As Provided
Reference Count: 15
ISSN: ISSN-1051-1970
Principal Component Analysis: Resources for an Essential Application of Linear Algebra
Pankavich, Stephen; Swanson, Rebecca
PRIMUS, v25 n5 p400-420 2015
Principal Component Analysis (PCA) is a highly useful topic within an introductory Linear Algebra course, especially since it can be used to incorporate a number of applied projects. This method represents an essential application and extension of the Spectral Theorem and is commonly used within a variety of fields, including statistics, neuroscience, and image compression. We present a synopsis of PCA and include a number of examples that can be used within upper-level mathematics courses to engage undergraduate students while introducing them to one of the most widely used applications of linear algebra.
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: National Science Foundation
Authoring Institution: N/A
Identifiers - Location: Colorado
Grant or Contract Numbers: DMS-1211667