Comparison of classical linear regression and orthogonal regression with respect to the sum of squared perpendicular distances

Abstract

Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it was seen that OR line has appeared to present a much better fit for the data than CLR line. Depending on those results, the OR is thought to be a regression technique to obtain more accurate results than CLR at simple linear regression studies.