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Syllabus

PNS0186 Statistics IV: Generalized Linear Models, 4.0 Credits

Subjects

Mathematical Statistics

Education cycle

Postgraduate level

Grading scale

Language

English

Prior knowledge

Statistics III: Regression Analysis or equivalent.

Objectives

The objective of the course is to give an overview of generalized linear models. On completion of the course, the student will be able to:

• specify generalized linear models including conditions and assumptions

• select an appropriate linear model for a given problem

• carry out an analysis based on a generalized linear model in the statistical software R or SAS

• interpret and evaluate results correctly and draw reasonable conclusions

• clearly and concisely communicate results and conclusions

Content

The course will cover the following topics:

• Binomial and multinomial logistic regression

• Poisson regression

• Overdispersion and zero-inflation.

• Generalized linear models and generalized linear mixed models.

Formats and requirements for examination

Passed exercises and passed examination in written and/or oral form.

• If a student has failed an examination, the examiner has the right to issue supplementary assignments. This applies if it is possible and there are grounds to do so.

• The examiner can provide an adapted assessment to students entitled to study support for students with disabilities following a decision by the university. Examiners may also issue an adapted examination or provide an alternative way for the students to take the exam.

• If this syllabus is withdrawn, SLU may introduce transitional provisions for examining students admitted based on this syllabus and who have not yet passed the course.

• For the assessment of an independent project (degree project), the examiner may also allow a student to add supplemental information after the deadline for submission. Read more in the Education Planning and Administration Handbook.

Responsible department

Department of Energy and Technology