Research Article
Oct 1974
Multivariate Techniques for Water Quality Analysis
Publication: Journal of the Environmental Engineering Division
Volume 100, Issue 5
Abstract
The objective of this study was to demonstrate the application of multivariate statistical techniques towards the understanding of variables affecting water quality. One of the major problems confronting an investigator in the application of statistical techniques to water quality data is missing observations. A simultaneous multiple regression method is presented in this paper for estimating missing observations in a data matrix. The major goals of using multivariate analysis are to facilitate interpretation and to prove hypotheses concerning the data. The techniques considered in this paper include principal components, canonical correlation, partial correlation, multivariate analysis of variance (MANOVA), and discriminant analysis. Examples are presented demonstrating the application of these methods.
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Published In
Journal of the Environmental Engineering Division
Volume 100 • Issue 5 • October 1974
Pages: 1119 - 1132
Copyright
© 1974 American Society of Civil Engineers.
History
Published in print: Oct 1974
Published online: Feb 11, 2021
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Authors
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Jerome L. Mahloch
Asst. Prof. of Civ. Engrg.; Mississippi State Univ., Mississippi State, MS, USA
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.