AM  Vol.5 No.5 , March 2014
Application of Multiple Linear Regression and Manova to Evaluate Health Impacts Due to Changing River Water Quality
Abstract: 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, 5, 799-807. doi: 10.4236/am.2014.55076.

[1]   Koklu, R., Sengorur, B. and Topal, B. (2010) Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey). Water Resource Management, 24, 959-978.

[2]   Mustapha, A. and Abdu, A. (2012) Application of Principal Component Analysis & Multiple Regression Models in Surface Water Quality Assessment. Journal of Environment and Earth Science, 2, 16-23.

[3]   Mustapha, A. and Aris, A.Z. (2012) Multivariate Statistical Analysis and Environmental Modeling of Heavy Metals Pollution by Industries. Polish Journal of Environmental Studies, 21, 1359-1367.

[4]   Pathak, H. (2012) Evaluation of Ground Water Quality Using Multiple Linear Regression and Mathematical Equation Modeling. Annals of the University of Oradea—Geography Series, 2, 304-307.

[5]   Pathak, H. (2013) Water Quality Studies of Two Rivers at Bundelkhand Region, MP, India: A Case Study. U.P.B. Science Bulletin, Series B, 75, 81-90.

[6]   Mohansingh, R., Fernandez, G.C.J. and Dennett, K.E. (2006) Using SAS for Statistical Modeling of Nutrient Removal and Water Quality Aspects from Constructed Wetlands. Statistics and Data Analysis, SUGI 31 Proceedings, 1-11.

[7]   Gyawali, S., Techato, K., Yuangyai, C. and Musikavong, C. (2013) Assessment of Relationship Between Land Uses of Riparian Zone and Water Quality of River for Sustainable Development of River Basin, A Case Study of U-Tapao River Basin, Thailand. The 3rd International Conference on Sustainable Future for Human Security SUSTAIN 2012, Procedia Environmental Sciences, 17, 291-297.

[8]   Eneji, I.S., Onuche, A.P. and Ato, R.S. (2012) Spatial and Temporal Variation in Water Quality of River Benue, Nigeria. Journal of Environmental Protection, 3, 915-921.