Entry requirements

Knowledge and achievements corresponding to passed 60 credits of natural science or technology, including basic course in analytical chemistry

Learning outcomes

After the course, the student should be able to

- identify factors and analyse their influence on chemical measurement data and chemical systems

- design and evaluate full and reduced factorial experiments

- describe strategies and apply methods for optimisation

- describe and apply multivariate projection methods for visualisation and empirical modelling (characterisation, classification, calibration)

- make use of computer programs for the above mentioned methods

Content

Statistical and mathematical methods (multi-way and hierarchical analysis of variance, multiple linear regression, response surface modelling, simplex optimisation, principal component analysis, partial least squares regression, clustering analysis) for empirical modelling of chemical/biological systems; with special attention to experimental design and multivariate data analysis. Exercises, seminars and miniprojects linked to complex problems within e.g. industrial processes, environment monitoring and biological/medical research.

Instruction

Lectures, seminars, computer exercises, miniprojects and home assignments. Compulsory moments are: course introduction, seminars, computer exercises (reports in writing) and miniprojects (oral presentations)

Assessment

The course marks are based on the results of a written examination arranged at the end of the course, the reports from the computer exercises, and the home assignments,