Entry requirements

120 credits including 90 credits mathematics with Regression analysis. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

On completion of the course, the student should be able to:

• give an account of the idea of generalising of linear modelling;
• find the right link function
• apply the maximum likelihood inference to general linear models;
• give an account of the quasi likelihood approach;
• carry out tests in general linear models;
• use R for analysing real data sets;
• be able to interpret the results in practical examples.

Content

Models with different link functions. Binary (logistic) regression, Estimation and model fitting. Residual analysis. Mixed effext models. Hierarchical models. Practical examples. R commands.

Instruction

Lectures and computer sessions.

Assessment

Written examination at the end of the course. Complulsory assignments during the course.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.