Assessment of Sediment Quality in Hussainsagar Lake and Its Inlet Channels Using Multivariate Statistical Techniques

2015 ◽  
Vol 6 (1) ◽  
pp. 762-766 ◽  
Author(s):  
Dr. A.Sridhar Kumar ◽  
Y. Seeta ◽  
M. Satyanarayana ◽  
Prof.P.Manikya Reddy
Keyword(s):  
Sediment Quality ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical

scholarly journals Evaluation of the anthropogenic impact in Suat Ugurlu Dam lake using multivariate statistical techniques

2018 ◽  
Vol 20 (1) ◽  
pp. 161-168 ◽  
Keyword(s):  
Anthropogenic Impact ◽  
Sediment Quality ◽  
Principal Component ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Cluster Number ◽  
Multivariate Statistical ◽  
Oxidation Reduction ◽  
Oxidation Reduction Potential ◽  
And Cluster Analysis

Sediments play an important role in the quality of aquatic ecosystems in the Dam Lake where they can either be a sink or a source of contaminants, depending on the management. This purpose of this study is to identify the sediment quality in order to find out the causes for the malodor and the eutrophication that is causing a bad scenario. Solutions for improving the dam are proposed. Multivariate statistical techniques, such as a principal component analysis (PCA) and cluster analysis (CA), were applied to the data regarding sediment quality in relation to anthropogenic impact in Suat Ugurlu Dam Lake. This data was generated during 2014-2015, with monitoring at four sites for 11 parameters. A PCA and CA were used in the study of the samples. The total variance of 84.1%, 74.3%, 87.4% and 91.5% suggest 4, 3, 3 and 4 principle components (PCs) in the four locations: LC1, LC2, LC3 and LC4, respectively. Also, a CA was applied to both the variables and the observations. Some variables and observations showed a high similarity based on the results of variables in the CA. Also, the similarity ratio of temperature-mercury (Hg) and oxidation reduction potential (ORP) was high and generally, the cluster number of variables was 5, according to the selected similarity level.

Assessing exercises recommended for women at risk of pelvic floor disorders using multivariate statistical techniques

2017 ◽  
Vol 29 (10) ◽  
pp. 1447-1454 ◽  
Author(s):  
Tania Tian ◽  
Stephanie Budgett ◽  
Jackie Smalldridge ◽  
Lynsey Hayward ◽  
James Stinear ◽  
...  
Keyword(s):  
At Risk ◽  
Pelvic Floor ◽  
Pelvic Floor Disorders ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical

Interactions of 2-PPM Lead in the Water Supply with Food Deprivation upon Maze-Swimming Behavior of Mice

1982 ◽  
Vol 55 (2) ◽  
pp. 515-519 ◽  
Author(s):  
S. Kowalski ◽  
G. H. Parker ◽  
M. A. Persinger
Keyword(s):  
Drinking Water ◽  
Water Supply ◽  
Food Deprivation ◽  
Tap Water ◽  
Swimming Behavior ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Food Condition ◽  
Ad Libitum

Mice that had been given either tap water or 2 ppm lead in their drinking water and either severely food deprived (3 days before testing) or allowed food ad libitum demonstrated significant interactions of lead treatment by day by food condition and lead by block. Although not statistically significant, the food deprived-lead treated mice displayed more errors and longer latencies than the ad libitum-water controls. The food deprived-water controls and ad libitum-lead-treated mice displayed intermediate values. The importance of using multivariate statistical techniques that can evaluate dynamic repeated behavioral measurements is emphasized.

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