General information

Module title Basics of Chemometrics
Language English
Module lecturer prof. zw. dr hab. Marek Kręglewski
Lecturer's email
Lecturer position profesor zwyczajny
Faculty Faculty of Chemistry
Semester 2021/2022 (summer)
Duration 30
USOS code 02-BCMA


Module aim (aims)

The course gives an introduction to practical and theoretical chemometric methods.
The student should be able to perform basic experimental design, analysis of variance, principal component analysis, multivariate regression and basic methods within cluster analysis and classification. The statistical software will be introduced to students.

Pre-requisites in terms of knowledge, skills and social competences (where relevant)


Week 1: What is Chemometrics? Introduction to Statistical software.
Week 2: Calibration methods: regression and correlation.
Week 3: Experimental design. Two-way Analysis of Variance
Week 4: Classification. Similarity. Data Transformation (scaling, standardization).
Week 5: Distance calculation between objects. Euclidean distance, the K-nearest neighbour method (KNN), the K-means method.
Week 6: Principal Component Analysis (PCA).
Week 7: Cluster Analysis (CA).
Week 8: Dendrograms.
Week 9: Multiple Linear Regression.
Week 10: Summary and exam.

Reading list

1. Alexey L. Pomerantsev, Chemometrics in Excel, Wiley 2014.
2. J. N. Miller, J.C. Miller, Statistics and Chemometrics for Analytical Chemistry, Pearson 2010.