Table of contents

The course is connected to the following study programs

Recommended previous knowledge

  • EX-602 Philosophy of Science
  • ME-626 General Quantitative Research Methods, ME-428 or corresponding courses

Learning outcomes

On successful completion of the course, the candidate has:

 

Knowledge about

  • assumptions for performing linear regression
  • strategies for model building
  • how to critically evaluate regression models and model fit
  • model assumptions

Skills

  • can evaluate initial data before analysis
  • can perform and report linear regression analysis with categorical and continuous independent variables

General competence

  • can independently plan, analyze, report and interpret own linear regression analysis and models
  • can interpret and critically evaluate linear regression analysis and models from published research

Contents

  • Assumptions for performing linear regression
  • Initial evaluation of data including cofounding variable
  • Analysis with continuous independent variables
  • Analysis with categorical independent variables
  • Strategies for model building
  • How to assess the model fit
  • Critical evaluation of models

Teaching and learning methods

Lectures combined with practical statistical exercises in a computer lab. Examples of analysis of data will to a great degree be connected to the faculty’s on-going or planned research projects.

Examination requirements

Participation in compulsory lectures as stated in the course pamphlet.

Examinations

Individual 5-days home examination. The examination will be assessed as pass/fail.
Last updated from FS (Felles studentsystem) Oct. 15, 2026 7:40:35 AM