Statistics for experimental medical researchers
Graduate School of Health and Medical Sciences at University of Copenhagen
This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH.
Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list.
The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee.
Aim
This five-day course on biostatistics aims at Ph.D. students in biomedical research who work in a laboratory or similar setting, performing experiments on e.g., cells, tissues, mice, or humans. When participating in this course, you will get a working knowledge of statistical concepts, methods of analysis, and adequate ways of presenting statistical results, as well as hands on experience in analysing experimental data with R statistical software. We will also explain some of the most common pitfalls in the statistical analysis of biomedical research data. In summary, we aim at teaching you high-quality biostatistics suitable for research publications.
Learning objectives
A student who has met the objectives of the course will be able to:
1. Have a qualified discussion with a statistical consultant, e.g., on how to plan the analyses for a research project or how to answer the concerns raised by a reviewer.
2. Interpret statistical information from research papers and discuss assumptions and limitations.
3. Distinguish between descriptive statistics and statistical inference (effect estimates, confidence intervals and p-values).
4. Apply basic statistical analyses to experimental data using the statistical software R.
5. Present statistical results in figures, tables, and words.
Content
Day 1: Data, descriptive statistics, statistical inference
Day 2: Testing statistical hypotheses, sample size and power calculation
Day 3: ANOVA and regression
Day 4: Repeated measurements
Day 5: Case study
Statistical software
We will be working with the open-source statistical software R using the interface R Studio. To participate in the course, you must bring your own laptop with R and R Studio installed.
Prerequisites
Familiarity with R programming is necessary for taking part in the exercise classes. We recommend the PhD course: Introduction to R for basic statistics which runs just before this course starts.
Participants
Ph.D.-students. In case of vacant seats also other medical researchers. Max. 30 participants.
Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:
All graduate programmes
Language
English
Form
The course includes lectures and computer exercises (please bring your own laptop) that demonstrate both the implementation and interpretation of key concepts. In addition, students are expected to engage in self-study and complete mandatory online home assignments (quizzes) via Absalon, the University of Copenhagen’s teaching platform, where discussion threads provide support. Exercises are based on the statistical software R. Active participation through homework and preparation is required, and successful completion of all online assignments is necessary to pass the course.
Course director
Thomas Alexander Gerds, Section of Biostatistics
Teachers
Alessandra Meddis, Section of Biostatistics
Thomas Alexander Gerds, Section of Biostatistics
Dates
6, 9, 20, 23, 27 October 2025, all days 8-12. Online homework assignments between these dates.
Course location
CSS
Registration:
Please register before 5 September 2025
Frequnecy
Once a year
Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrollment.
Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.