MEENU SHARMA AND VIPIN VYAS
Abstract
Principal Component Analysis (PCA) multivariate statistical tool can be used to reduce the dimensionality of data set and maintain the characteristics of variables which contribute mostly to this variation. The aim of the present study is to assess the groundwater quality of twenty-four sampling sites which surrounds Mandideep Industrial Estate, Raisen district in winter season. Fourteen physico-chemical parameters such as pH, TDS, DO, conductivity, chloride, alkalinity, total hardness, sulphate, nitrate, fluoride, iron etc. have been studied to determine the groundwater quality. PCA was applied on experimental data using SPSS, Version 20 software. The outcome of PCA revealed that TDS, total hardness, chloride, sulphate, pH and DO affect the groundwater quality. Further, it also revealed that most of the samples are not suitable to use for drinking purpose without any treatment.