Entry requirements

Probability theory MN1 and Inference theory MN1.

Probability theory MN2, Inference theory

NV2 and Regression analysis MN1 are recommended.

Aims

To give knowledge and skills in analysis of variance and the design of experiments.

Content

Analysis of variance, one-way and two-way

classifications. Multiple comparisons. Variance

components. Hierarchical models. Complete

randomisation, block experiments and factor

experiments. Latin squares. Experiments with

incomplete blocks. Split-plot experiments.

Analysis of covariance. Introduction to

statistical software packages.

Instruction

Lectures, problem solving sessions and

laboratory sessions.

Assessment

Written and, possibly, supplementary oral

examination at the end of the course. Moreover,

compulsory assignments may be given during the

course.