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The Chemical Educator

ISSN: 1430-4171 (electronic version)

Table of Contents

Abstract Volume 10 Issue 5 (2005) pp 337-345

Using Univariate Linear Regression Calibration Software in the MATLAB Environment. Application to Chemistry Laboratory Practices

Anunciación Espinosa-Mansilla,* Arsenio Muñoz de la Peña, and David González-Gómez

Department of Analytical Chemistry, University of Extremadura, 06071, Badajoz, Spain, nuncy@unex.es
Received September 16, 2004. Accepted January 28, 2005.

Published online: 8 August 2005

Abstract. A useful software package for statistical analysis by univariate linear regression calibration is presented in this paper. In many chemistry laboratory experiments, a linear-regression calibration is needed to fit the experimental results to a linear model. An example of this is the common use of UV–visible molecular absorption spectroscopy and the application of the Lambert–Beer law, which establishes a linear relationship between the concentration of an absorbent analyte and its absorbance measured at a specific wavelength. A great number of commercial statistical software packages exist. We present here, a home-made one, developed with two principal aims: first, to show students how to create their own software to resolve a specific statistical calculation problem, and, second, to include in the same software package all of the major statistical methods useful to analytical chemistry students. All the calculations are performed with suitable routines written for the MATLAB programming environment. MATLAB allows the calculation and resolution of complex equations with very simple programming commands. An easy experiment is presented to show how to use the software. The experiments presented may be performed in an analytical chemistry course. They can be completed in four hours with the analysis of the data using the software package requiring an additional 4-hour computational class session.

Key Words: Laboratories and Demonstrations; analytical chemistry; instrumental analysis; computers

(*) Corresponding author. (E-mail: nuncy@unex.es)

Article in PDF format (420 KB) HTML format

Supporting Materials:

 

Supporting Materials:

A listing of the MATLAB code for running ACOC and example files are available. The software is included in a self-extracting Zip file (acoc.exe). (49 KB)


Issue date: October 1, 2005

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