Related Experiment Video
Updated: May 29, 2026

Measurements of Soil Water Potential and Conductivity based on a Simple Evaporation Experiment using a Hydraulic Property Analyzer
Published on: August 9, 2024
A correlation-regression model for the physicochemical parameters of the groundwater in Coimbatore city, India
1School of Civil Engineering, Karunya University, Coimbatore, India. piya_kl@yahoo.co.in
Abstract:
The textile hub of Coimbatore city is facing a serious water pollution problem, both for surface water and groundwater. Industrial and domestic waste is continuously discharged into surface water bodies, resulting in the degradation of groundwater quality. In order to assess the quality of groundwater, the Singanallur area was selected for the present study. The quality of groundwater is worse in this area and the physicochemical parameters exceed the permissible limits of the Indian drinking water standards. The water type of the study area was predominantly NaCl and MgCl. A statistical analysis was carried out to understand the linear relation between the best correlated parameters. The relationship for different parameters for the study area was analysed for two seasons, pre-monsoon and post-monsoon, because the water quality varies widely seasonally. The study showed that there is a good and equal correlation between total hardness and calcium, total hardness and magnesium, and calcium and magnesium in both time periods. The relationship can be utilized to determine the value of calcium and magnesium when the value of total hardness is known for the study area. Cluster analysis was performed to obtain a dendrogram for the study area, from which the source of pollution was identified for different regions.
Related Concept Videos
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Correlation and Regression
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Drug Product Performance: In Vitro–In Vivo Correlation
Calculating and Interpreting the Linear Correlation Coefficient
Model Approaches for Pharmacokinetic Data: Physiological Models

