At the end of the course, the student must be able to critically deal with a validation process and be aware of the tools offered by chemometrics for visualizing large data sets, including the possibility of classifying and quantifying multivariate responses.
Course Prerequisites
Knowledge of univariate basic statistics, and calculation programs (Excel).
Teaching Methods
The course offers a wide range of exercises in the computer lab, performed in the first person by the student on data sets provided by the teacher. The various stages of validation will be covered. Excel and open-source chemometrics software will be employed and introduced to students through a variety of hands-on exercises.
Assessment Methods
The exam consists of evaluating laboratory activities and a personal production, which will be presented during the oral exam at the end of the course.
Texts
E. Desimoni, B. Brunetti, “L'elaborazione dei dati nel laboratorio di analisi chimiche”, Bologna, CLUEB, 2010. R. Todeschini, “Introduzione alla chemiometria”, Napoli, EdiSES, 1998.
Contents
The first part of the course deals with the procedures for an analytical method validation employed in chemical analysis, in detail referred selectivity, accuracy, precision, uncertainty, robustness and recovery. In the second part, the topics related to the multivariate structure of data and multidimensional dataset visualization are illustrated. Unsupervised techniques will be introduced with ample emphasis on the principal component analysis, PCA, 3wayPCA, and supervised, qualitative (classification) and quantitative techniques (Partial Least Square Regression, PLS).
