Regression and Residual Analysis in the Spectroscopic Study of Conjugated Dyes

The study of conjugated dyes within the framework of the one-dimensional particle-in-a-box (1D PIB) model is a fundamental experiment in undergraduate physical chemistry curricula. This work extends the analysis of this commonplace experiment with the inclusion of regression and residual analysis, which allows students to explore data fitting, parameterization, and model testing in a controlled fashion. The work herein describes an instructor-led activity to optimize an empirical factor used in a 1D PIB model for a series of cyanine dyes and their respective visible absorption spectra. Students gain experiential use of regression and residual analysis within a process that facilitates a consistent experience for all, independent of the quality of data collected. This makes for an effective educational tool for teaching regression and residual analysis and model parameterization.

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Publication Details

Journal
Journal of Chemical Education
Published
2026-07-16
DOI
https://doi.org/10.1021/acs.jchemed.5c01744
Primary Topic
Various Chemistry Research Topics
Type
article
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article

Regression and Residual Analysis in the Spectroscopic Study of Conjugated Dyes

Paul D. Cooper
Journal of Chemical Education
Various Chemistry Research Topics
article

Regression and Residual Analysis in the Spectroscopic Study of Conjugated Dyes

Paul D. Cooper
article en

Abstract

The study of conjugated dyes within the framework of the one-dimensional particle-in-a-box (1D PIB) model is a fundamental experiment in undergraduate physical chemistry curricula. This work extends the analysis of this commonplace experiment with the inclusion of regression and residual analysis, which allows students to explore data fitting, parameterization, and model testing in a controlled fashion. The work herein describes an instructor-led activity to optimize an empirical factor used in a 1D PIB model for a series of cyanine dyes and their respective visible absorption spectra. Students gain experiential use of regression and residual analysis within a process that facilitates a consistent experience for all, independent of the quality of data collected. This makes for an effective educational tool for teaching regression and residual analysis and model parameterization.

Journal of Chemical Education
Yale University (US)
Quality Education
Openalex Percentile: Top 10%
Various Chemistry Research Topics
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