Seminar Series: Statistics in Clinical Research


Course description

The course focuses on the most important statistical aspects and methods in clinical research. Through the course, participants will develop an understanding and critical evaluation of the statistical methods used in scientific publications. They will learn to develop a scientifically and statistically solid research question and analysis plan, and get an introduction to the correct use and interpretation of the most important statistical tools in clinical research.

Main topics covered during this course are: building a research question; study design; descriptive statistics; hypothesis testing, p-values and confidence intervals; diagnostic measures; linear and logistic regression; survival analysis; writing a statistical analysis plan.

Students will also get the opportunity to bring and discuss own cases and topics.

Course structure

This 9-week course requires students to attend a 1.5-hour session per week (1-hour session on the specific topic of the week + 0.5-hour of discussion).  

Recommended reading

Will be announced in due time per session.

Course dates

Tuesdays, 15.30 - 17.00h

Session 1 (October 22, 2024)

The scientific method and building a research question

Session 2 (October 29, 2024)

Descriptive statistics, data  presentation and visualisation

Session 3 (November 5, 2024)

P-values and confidence intervals

Session 4 (November 12, 2024)

Diagnostic measures

Session 5 (November 19, 2024)

Linear (multiple) regression

Session 6 (November 26, 2024)

Logistic regression

Session 7 (December 3, 2024)

Time-to-event/Survival analysis

Session 8 (December 10, 2024)

Writing a statistical analysis plan

Session 9 (December 17, 2024)

Bring your own research!

Please note that the detailed course progamme is subject to change.

Attending single sessions is possible if the course is not fully booked.
For information on free seats please contact Michael Coslovsky after the expiration of the registration deadline.



Sitzungszimmer, Spitalstr. 8, EG right (raised ground floor), 4056 Basel

Target audience/prerequisites for attending

Doctoral students in Medicine and PhD students of the PhD subject Clinical Research enrolled at the University of Basel, Faculty of Medicine. Moreover, PhD students of the other PhD subjects of the Faculty of Medicine (Biomedical Engineering, Biomedical Ethics, Medicines Development, Nursing Science, Public Health/ Epidemiology or Sport Science) are eligible to register for the course. If the course should not be fully booked, we are happy to welcome all other persons interested.

Minimum 8 and maximum 20 registered participants.

Learning objectives:

Upon successful completion of this course, the students will able to

  1. Understand the principals of the scientific method
  2. Develop a scientifically and statistically solid research question
  3. Critically evaluate statistical methods used in scientific publications
  4. Choose the correct analysis approach for their research question and write a detailed analysis plan
  5. Assess available resources offered by the DKF for their research projects


Work load and credits

Maximum of 15 hours of work load distributed over 9 weeks.  Attendance to all but two sessions is required for acquiring a certificate of attendance.

Note for PhD students: The workload of this course will be tranfered into ECTS credits automatically if the course is listed in your approved learning agreement.

Assessment format


Study direction

Michael Coslovsky, PhD
Teamleader Data Analysis/Statistics, Department of Clinical Research

Teaching staff

Michael Coslovsky, PhD
Marco Cattaneo, PhD, Senior Statistician, Department of Clinical Research
Nikki Rommers, PhD, Statistician, Department of Clinical Research
Deborah Vogt, PhD, Senior Statistician, Department of Clinical Research


Mareike Gräter
Training and Education, Department of Clinical Research


The course is free of charge.


Course language is English.
Certificate of attendance will be issued after successful course completion (at least 7 sessions out of 9).
There will be no option to participate in the course online.


If you are interested in the course, please register here.