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Statistics for Medical Research with R

medRSD Workshop
Target group Doctoral students in medicine (Members of medRSD)
Supervisors and Postdocs
Scientific researchers
Language English, German
Length of the workshop One day
Places 10
Costs 250 € for external participants
Free for doctoral students and researchers at the Medical Faculty of HHU
Registration medRSD: See below how to register

In the training program of medRSD:
1 event days in the area of core competencies
In the basic curriculum of the PhD program:
1 event days after consultation with Dr. Gätjens

PD Dr. rer. nat. Pablo E. Verde
Koordinierungszentrum für Klinische Studien (KKS)
Leiter AG Biometrie


  1. The course introduces data analysis, data visualization, experimental design and statistical modeling with the free open source software R.
  2. We will learn the syntax of the R language together with a GUI (Graphical User Interface) which greatly simplify the application of the R language.
  3. All case studies are based on real data, either from medical publications or from previous research projects. We pay special attention to the presentation, reporting and interpretation of results.


The course is primarily aimed at medical researchers, whether clinical or non-clinical, and doctor students who need to perform statistical data analysis. It is expected that participants have a well working knowledge in data management and data visualization with Excel. It is an advantage to have previous experience with other data analysis software (e.g. SPSS).
We present statistical methods in some detail, but it is assumed that during undergraduate studies participants have completed an introductory course in probability and statistics.


Lecture 1: Getting started with R
Lecture 2: Introduction to data management with R
Lecture 3: Summarizing data and graphical data analysis
Lecture 4: Probability models and fitting probability distributions to data
Lecture 6: Association, prediction, and agreement between two variables
Lecture 5: Principles of experimental design, randomization and comparing groups
Lecture 7: Multiple regression modeling and variables selection
Lecture 8: Modeling survival and time to event data


Altman, Douglas G. (1999). Practical Statistics for Medical Research. Chapman & Hall/CRC.
Crawley, Michael (2014). Statistics: An Introduction Using R (second edition). Wiley.
Fox, John (2016). Using the R Commander: A Point-and-Click Interface for R. Chapman & Hall/CRC.

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