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 student has:

 

Knowledge about

  • the assumptions with respect to logistic regression
  • logistic regression models

Skills

  • can perform and critically evaluate logistic regression analysis with categorical and continuous independent variables
  • can predict outcomes with respect to sensitivity and specificity as well as predictive values

General competence

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

Contents

  • Assumptions for performing logistic regression
  • Analysis with categorical independent variables
  • Analysis with continuous independent variables
  • Critical evaluation of models
  • Prediction of outcome with respect to sensitivity and specificity as well as predictive values

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 7:40:34 AM