CALCULATING CONCENTRATIONS USING BEER-LAMBERT’S LAW AND LINEAR REGRESSION

Abstract

The article demonstrates an indirect method for determining the concentration of a substance in a solution by applying Beer-Lambert’s law and linear regression.

In chemistry and biochemistry, quantitative analysis of chemical concentrations is a fundamental task that often cannot be implemented through direct weighing. Therefore, we used Beer-Lambert’s law and regression techniques to construct a calibration curve that models the linear relationship between absorbance and concentration based on spectrophotometric data. Afterthat, the resulting linear regression model is then used to predict the unknown concentration given its measured absorbance.