Statistical methods for the SCIENCE
PhD School at the Faculty of SCIENCE at University of Copenhagen
This is a toolbox course where 80% of the seats are reserved for PhD students enrolled at the Faculty of SCIENCE at UCPH and 20% of the seats are reserved for PhD students from other Danish Universities/faculties (except CBS). Seats will be allocated on a first-come, first-served basis and according to the applicable rules.
Anyone can apply for the course, but if you are not a PhD student at a Danish university (except CBS), you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to applicants on the waiting list.
Aim and Content
In this course, students are assumed to be familiar with basic concepts of normal linear mixed effects models (e.g. as taught in the Statistics-variant of “Fundamentals of the PhD Education at SCIENCE – Module 2”). But to recap and extend the concepts of normal linear mixed effects models the course begins with an extension of the models with normally distributed responses (end-points) to similar models with binary, ordinal and counting responses. After this we will focus on three statistical data analysis challenges that often appear in biology, medicine, and other empirical sciences; (1) statistical analysis of multivariate responses, (2) statistical analysis of repeated measurements over time, (3) in depth understanding of the multiple testing problem and associated choices needed in addressing this problem in relation to the underlying scientific questions.
Learning outcomes
Intended learning outcome for the students who complete the course:
Knowledge:
• Understand elements of frequentist statistics including estimation, confidence intervals, hypothesis tests, model validation.
• Understand data types and organization in tidy data.
• Understand assumptions and limitations for statistical analyses.
• Understand data structures for multivariate and repeated measurements data.
• Understand the multiple testing problem and possible solutions.
Skills:
• Identify the structure and experimental design of a particular dataset.
• Choose an adequate statistical model for multivariate data.
• Choose an adequate statistical model for repeated measurements.
• Choose an adequate method for correcting for multiple testing.
• Use R via the RStudio interface to perform the statistical analysis.
Competences:
• Formulate scientific questions in terms of statistical hypothesis.
• Conduct statistical analysis using the discussed models.
• Interpret the results of a statistical analysis.
• Critically reflect over the results, conclusions and limitations of a statistical analysis.
• Judge when to seek help from a skilled statistician.
Target Group
All PhD students who use statistical methods to analyze quantitative data.
Recommended Academic Qualifications
This course builds upon the Statistics-variant of “Fundamentals of the PhD Education at SCIENCE – Module 2”. But everyone with an understanding of basic statistical models and methods, and basic skills in using R may benefit from the course.
Research Area
All SCIENCE research fields, and secondarily other scientific fields with a statistical data analysis element (e.g. health sciences).
Teaching and Learning Methods
The teaching is done as a mixture of lectures and hands-on exercises on data examples. The exercises usually involve using R via the RStudio interface.
Type of Assessment
Pass by attendance on minimum 4 of the 5 course days.
Literature
Will be announced later.
Course coordinator
Professor Bo Markussen (bomar@math.ku.dk)
Dates
2 + 3 days in two consecutive weeks:
Wednesday, October 28, 2026
Thursday, October 29, 2026
Wednesday, November 4, 2026
Thursday, November 5, 2026
Friday, November 6, 2026
Expected frequency
Annually
Third and Second week before the beginning of block 2
Course location
Either Frederiksberg or Nørre Campus.
Course fee
• Participant fee: 0 DKK
• PhD student enrolled at SCIENCE: DKK 0
• PhD student from Danish PhD school Open market: DKK 0
• PhD student from Danish PhD school not Open market: DKK 3.000
• PhD student from foreign university: DKK 3.000
• Master's student from Danish university: DKK 0
• Master's student from foreign university: DK 3.000
• Non-PhD student employed at a university (e.g., postdocs): DKK 3.000
• Non-PhD student not employed at a university (e.g., from a private company): 8.400
Cancellation policy
• Cancellations made up to two weeks before the course starts are free of charge.
• Cancellations made less than two weeks before the course starts will be charged a fee of DKK 3.000
• Participants with less than 80% attendance cannot pass the course and will be charged a fee of DKK 5.000
• No-show will result in a fee of DKK 5.000
• Participants who fail to hand in any mandatory exams or assignments cannot pass the course and will be charged a fee of DKK 5.000
Course fee and participant fee
PhD courses offered at the Faculty of SCIENCE have course fees corresponding to different participant types.
In addition to the course fee, there might also be a participant fee.
If the course has a participant fee, this will apply to all participants regardless of participant
type - and in addition to the course fee.