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Multivariate Analysis: Factor and Discriminant Analyses

Multivariate Analysis: Factor and Discriminant Analyses

Murat Yazici
Copyright: © 2019 |Pages: 24
ISBN13: 9781522535348|ISBN10: 1522535349|ISBN13 Softcover: 9781522588511|EISBN13: 9781522535355
DOI: 10.4018/978-1-5225-3534-8.ch003
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MLA

Yazici, Murat. "Multivariate Analysis: Factor and Discriminant Analyses." Machine Learning Techniques for Improved Business Analytics, edited by Dileep Kumar G., IGI Global, 2019, pp. 40-63. https://doi.org/10.4018/978-1-5225-3534-8.ch003

APA

Yazici, M. (2019). Multivariate Analysis: Factor and Discriminant Analyses. In D. G. (Ed.), Machine Learning Techniques for Improved Business Analytics (pp. 40-63). IGI Global. https://doi.org/10.4018/978-1-5225-3534-8.ch003

Chicago

Yazici, Murat. "Multivariate Analysis: Factor and Discriminant Analyses." In Machine Learning Techniques for Improved Business Analytics, edited by Dileep Kumar G., 40-63. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-3534-8.ch003

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Abstract

Multivariate analysis is based on the statistical principle of multivariate statistics, which includes observation and analysis of statistical output variables in case of more than one output variable at a time. The technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest in design and analysis. This chapter includes the theoretical concepts of multivariate analysis including factor and discriminant analyses. It is also gives examples to understand and apply them correctly.

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