SAGE Reference - Encyclopedia of Research Design

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Principal Components Analysis

In: Encyclopedia of Research Design
Edited by: Neil J. Salkind
Subject:Research Design
Keywords:principal component analysis

Also known as empirical orthogonal function analysis, principal components analysis (PCA) is a multivariate data analysis technique that is employed to reduce the dimensionality of large data sets and simplify the representation of the data field under consideration. PCA is ...

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  Salkind, N. J. (2010). Principal components analysis. In Encyclopedia of research design (Vol. 1, pp. 1098-1102). SAGE Publications, Inc., https://dx.doi.org/10.4135/9781412961288.n334
  
  Salkind, Neil J. "Principal Components Analysis." In Encyclopedia of Research Design, edited by Salkind, Neil J., 1098-102. Thousand Oaks, CA: SAGE Publications, Inc., 2010. https://dx.doi.org/10.4135/9781412961288.n334.
  
  Salkind, N. J. 2010. Principal Components Analysis. In: Neil J. Salkind Editor, 2010. Encyclopedia of Research Design, Thousand Oaks, CA: SAGE Publications, Inc. pp. 1098-1102 Available at: <https://dx.doi.org/10.4135/9781412961288.n334> [Accessed 27 May 2022].
  
  Salkind, Neil J. "Principal Components Analysis." Encyclopedia of Research Design. Edited by Vol. 1. Thousand Oaks: SAGE Publications, Inc., 2010, pp. 1098-102. SAGE Knowledge. 27 May 2022, doi: https://dx.doi.org/10.4135/9781412961288.n334.
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