10.46243/jst.2020.v5.i4.pp268-275 registered

: This Study Statistically analyzes the deteriorating water quality of the River Ganga. Statistical techniques such as Water Quality index (WQI), Cluster Analysis, Best Subsets Regression and Multiple Regression Analysis were applied to seven water quality parameters, collected from 21 sampling Stations in India. Water Quality Index identified the most polluted stations that are Kadaghat, Allahabad, Khurgi, Patna U/S, Bihar, Varanasi D/S (Malviya Bridge), U.P, Indrapuri, Dehri and Varanasi U/S (ASSIGHAT), U.P. Cluster Analysis for the different Stations showed a similarity of 99.99% between the stations Ganga D/S, Mirzapur , Varanasi D/S (Malviya Bridge) and Varanasi U/S (Assighat), U.P. Cluster Analysis for variables showed a 98.96% similarity of parameter BOD with WQI and 96.06% similarity between the parameters Total Coliform and Fecal Coliform. After applied the Best Subset Regression Analysis we get the highest Mallow c-p value with high R2 for the parameters BOD, Nitrate, Total Coliform and Fecal Coliform. In the Regression analysis the p value for the estimated coefficients of BOD is 0.00, indicates that BOD is significantly related to WQI.In this paper we conclude that BOD is the most critical parameter and we study the comparison of water quality of river Ganga for different stations.