Rivers are important systems which provide water to
fulfill human needs. However, excessive human uses
over the years have led to deterioration in quality of river causing, causing
health problems from contaminated water. This study focuses on the application
of statistical techniques, Multiple Linear Regression model and MANOVA to
assess health impacts due to pollution in Cauvery river stretch in
Srirangapatna. In this study, using Multiple Linear Regression, it is found
that health impact level is 60.8% dependent on water quality parameters of BOD,
COD, TDS, TC and FC. The t-statistics
and their associated 2-tailed p-values
indicate that COD and TDS produces health impacts compared to BOD, TC and FC,
when their effects are put together across all the six sampling stations in
Srirangapatna. Further Pearson correlation Matrix shows highly significant positive
correlation amongst parameters across all stations indicating possibility of
common sources of origin that might be anthropogenic. Also graphs are plotted
for individual parameters across all stations and it reveals that COD and TDS values
are significant across all sampling stations, though their values are higher in
impact stations, causing health impacts.
Cite this paper
Basu, S. and Lokesh, K. (2014) Application of Multiple Linear Regression and Manova to Evaluate Health Impacts Due to Changing River Water Quality. Applied Mathematics
, 799-807. doi: 10.4236/am.2014.55076
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