Chemometric statistical techniques were applied for the evaluation and interpretation of a large complex water quality data set of Vaigai river in South India, monitoring 20 parameters at four different sites in quarterly basis. Principal component analysis resulted in three principal components (PC) explaining 99.9% of the total variance in water quality. The factors indicate that the possible variances in water quality may be due to either sources of anthropogenic origin or due to different biochemical processes that are taking place in system. All datasets were subjected to compute correlation and water quality index (WQI). WQI exceeded WHO permissible limit of 100, indicating that the water samples were unfit for human consumption, rearing of wild life and can be used for irrigation. Regression analysis revealed greater influence of alkalinity and BOD in determination of WQI. This study illustrates the benefits of Chemometric statistical techniques for determination of water quality.