SUBJECT

Title

Chemometrics

Type of instruction

practical

Level

Master

Faculty

Faculty of Science

Part of degree program

Credits

Recommended in

Semester 2/4

Typically offered in

Spring semester

Course description

Introduction into singlevariate and multivariate statistical analysis of chemical data. Singlevariate statistics, distributions, statistical parameters, definitions in analytical chemistry, tests. Multivariate data structures, data vectors. Clustering and classification. principal component analysis. Modelling. OLS regression. Biased regression. Partial least squares. Robust regression. Nonlinear regression. Analysis of variance and covariances. design of experiment.

Readings

Compulsory:

Syllabus of the lecturer Suggested: I Frank and R Todeschini: Data Analysis Handbook, Elsevier, Amsterdam, 1994
S. Dowdy, S. Wearden: Statistics for research, Wiley, New York, 1983
L. Eriksson et al.: design of experiments, Umetrics, Umea, 2008