Entry requirements

60 credit points Mathematics including Inference Theory

Learning outcomes

In order to pass the course (grade 3) the student should be able to

• perform simple and multiple linear regression;
• describe and use the general linear model;
• perform residual analysis and transformations of variables;
• handle non-linear regression;
• use methods based on orthogonal polynomials;
• perform one-way and multi-way analysis of variance;
• give an account for various designs of experiments: complete randomisation, blocks and factors, Latin squares, incomplete blocks;
• perform analysis of covariance;
• use statistical software for analysis of regression and variance;
• give examples of statistical methods from the professional career.

Content

Regression: simple and multiple linear, nonlinear, transformation of variables, residual analysis, orthogonal polynomials. Analysis of variance: one-sided, multivariate, multiple comparisons, variance component models. Design of experiments: randomisation, blocks, factors. Use of statistical software.

Instruction

Lectures, problem solving sessions and computer-assisted laboratory work.

Assessment

Written examination in the end of the course combined with assignments given during the course.