A practitioner’s guide for exploring water quality patterns using principal components analysis and Procrustes

2016 ◽  
Vol 188 (4) ◽  
Author(s):  
C. J. Sergeant ◽  
E. N. Starkey ◽  
K. K. Bartz ◽  
M. H. Wilson ◽  
F. J. Mueter
Keyword(s):  
Water Quality ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Components Analysis

scholarly journals Multivariate Statistical Analysis Applied to Water Quality of a Tropical Coastal Lagoon, Cartagena, Colombian Caribbean

2019 ◽  
Vol 20 (1) ◽  
pp. 141
Author(s):  
Ildefonso Baldiris-Navarro ◽  
Juan Carlos Acosta-Jimenez ◽  
Angel Dario Gonzalez-Delgado ◽  
Alvaro Realpe-Jimenez ◽  
Juan Gabriel Fajardo-Cuadro
Keyword(s):  
Water Quality ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Coastal Lagoon ◽  
Coastal Lagoons ◽  
Oxygen Demand ◽  
Habitat Destruction ◽  
Environmental Data ◽  
Fecal Coliforms ◽  
Components Analysis

Coastal lagoons are one of the most threatened ecosystems in the world, because of population growth, habitat destruction, pollution, wastewater, overexploitation and invasive species which are the main causes of their degradation. The objective of this paper was to evaluate the water quality behavior in a stressed coastal lagoon in Cartagena, Colombian Caribbean. Environmental data was analyzed using hypothesis testing, confidence intervals, and also Principal components analysis (PCA). The study was focused on water parameters such as dissolved oxygen (DO), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), salinity, pH, total dissolved solids, total coliforms (TC), Fecal coliforms (FC), ammonium (NH4+) and total phosphorus (TP). The analysis was conducted in line with the Colombian national water standard. Results showed that BOD5, COD, phosphorus, and coliforms are out of the limits for these variables in Colombia and are reaching levels that may be a threat to human health. Principal components analysis detected five components that explained 79.4% of the variance of data and showed that anthropogenic and temporal factors might be affecting the variation of the parameters.

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

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