A General Study on Regression Analysis (RA)

Abstract

Regression analysis constitutes a collection of statistical methodologies employed for the estimation of relationships between a dependent variable and one or several independent variables. The Regression Analysis (RA) generates a series of regression equations wherein the coefficients signify the relationship between each independent variable and the dependent variable. Regression analysis mainly consist of 2 important function known as the primary and the secondary function. In the primary function first RA is used for predicting and forecasting the places where its uses overlap with that of the machine learning (ML) field. In the secondary function it tries to infer in the association between the dependent variable and the independent variable is examined. This research paper endeavors to elucidate the intricacies of regression analysis comprehensively. The unknown coefficients are determined utilizing the data obtained from experiments or alternative sources, employing Legendres principle of least squares errors. In this document, regression equations have been employed to forecast the ultimate load and ultimate deflection values. Then later the predicted value was compared with the experimental value and the result of it was displayed in further sections.