After successful completion of the course, students are able to correctly apply the most important methods of chemometrics. The practical approach of the course enables the students to gather experience in data analysis based on specific datasets.

Basic concepts of statistics, visualisation of data, descriptive statistics, statistical tests, time series, factorial design, regression models, multivariate models, selection of variables, calibration, analysis of time series, validation of models, MLR, principal component analysis, factor analysis, PCR, PLS, discriminant analysis, clustering, hyperspectral imaging

Theoretical lectures in combination with practical exercises.

written exam at the end of the semester