27th Nov 2023

Regression modeling is a statistical approach used to investigate and quantify the relationship between a dependent variable and one or more independent variables. It assumes a functional form, typically linear, where the model estimates coefficients for each independent variable to describe the impact of changes in these variables on the dependent variable. The aim is to create a predictive model that minimizes the difference between the predicted and actual values of the dependent variable, providing insights into the nature and strength of the relationships observed in the data.

Widely employed in fields such as economics, biology, and social sciences, regression modeling enables researchers to derive meaningful interpretations from observed data. It serves as a versatile tool, adaptable to different scenarios, allowing for the incorporation of multiple independent variables or the exploration of nonlinear relationships. With its ability to provide both explanatory and predictive power, regression modeling remains a foundational method in statistical analysis, aiding in understanding complex relationships and making informed decisions based on empirical evidence.