Principal Component Analysis: Resources for an Essential Application of Linear Algebra

Autor/inn/en	Pankavich, Stephen; Swanson, Rebecca
Titel	Principal Component Analysis: Resources for an Essential Application of Linear Algebra
Quelle	In: PRIMUS, 25 (2015) 5, S.400-420 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1051-1970
DOI	10.1080/10511970.2014.993446
Schlagwörter	Factor Analysis; Mathematics Instruction; College Mathematics; Algebra; Introductory Courses; Teaching Methods; Undergraduate Study; Mathematical Concepts; Theories; Mathematical Logic; Problem Solving; Equations (Mathematics); Neurosciences; Visual Aids; Colorado + Suchen Sie Ihr Suchwort? Faktorenanalyse; Mathematics lessons; Mathematikunterricht; Einführungskurs; Teaching method; Lehrmethode; Unterrichtsmethode; Grundstudium; Theory; Theorie; Mathematical logics; Mathematische Logik; Problemlösen; Equations; Mathematics; Gleichungslehre; Neuroscience; Neurowissenschaften; Neurowissenschaft; Anschauungsmaterial
Abstract	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. (As Provided).
Anmerkungen	Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01