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Syllabus

PNS0180 Statistics III: Regression analysis, 4.0 Credits

Subjects

Mathematical Statistics

Education cycle

Postgraduate level

Grading scale

Language

English

Prior knowledge

Statistics I: Basic Statistics or equivalent

Objectives

The objective of the course is to give an overview of linear, nonlinear and nonparametric regression. On completion of the course, the student will be able to:

• specify regression models including conditions and assumptions

• select an appropriate regression model for a given problem

• carry out a regression analysis 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:

• Simple linear regression.

• Multiple linear regression.

• Nonlinear models.

• Nonparametric regression and generalized additive models (GAM).

• Analysis of residuals.

Formats and requirements for examination

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• If this syllabus is withdrawn, SLU may introduce transitional provisions for examining students admitted based on this syllabus and who have not yet passed the course.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 examination of a degree project (independent project), the examiner may also allow the 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