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Introduction to the statistical software R


  • Good general PC knowledge
  • Programming skills is an advantage
  • Basic statistical knowledge is required

Concept of the course:

“R” (https://www.r-project.org/) is a programming language and application environment for statistical analyses and graphics. R is a free GNU project software and can be installed and used free of charge. Unlike many commercial systems (e.g. SPSS, SAS), the R-project is constantly developed by leading scientists and the wide statistical community. All procedures and functions are visible, i.e. the source code can be called up and checked at any time. There are a lot of packages that cover literally all statistical questions and methods.

The seminar gives a first impression of the R functionality and how to deal with a scripting language. The workshop is application-oriented. Standard procedures in R are shown and trained by means of examples and own calculations on a learning dataset. During the first two days the basic knowledge of R is given. The third day could be interesting for advanced users as well.

The participants are required having basic statistical knowledge before being enrolled. The statistical methods and its purpose will be not discussed in the course but only their application in R.

Learning aims:

  • Operate with objects, vectors and matrices. Import and export from/to SPSS and Excel sheets. Basic data management and data types. Basic arithmetic operations, data handling and transforming.
  • Making simple and complex graphics, running simple and sophisticated descriptive and inferential statistical analysis.
  • Understanding how the complex statistical analysis can be performed in R (linear and logistic regressions).

Course content:

  • Brief introduction to R, the concept of R and the basic functions and conventions
  • Working with RStudio
  • Practical exercises with simple calculations and application procedures
  • Getting to know simple basic vocabulary of the script language
  • Reading complex data records
  • Data sorting and data retrieval
  • Explorative data analysis: hypothesis testing, confirmatory data analysis
  • Creating custom functions
  • Creating graphics: simple and complex (gglopts)
  • Creating descriptive and inferential statistical procedures (power analysis).
  • Basic regression analysis in R, diagnostic techniques for the quality of regressions, statistical testing, diagrams.


The program can be installed on participants’ own laptops:

YouTube how-to-do for Windows 10: https://www.youtube.com/watch?v=_2sewGCA0y4&ab_channel=BecomingaDataScientist

YouTube how-to-do for Mac OS: https://www.youtube.com/watch?v=LanBozXJjOk&ab_channel=DataSciencewithTom

Please install R first and then RStudio. The programs must be granted administrator rights in Windows 7 or higher operating system versions. Installation on Mac OS is also possible.


1. Dr. Katherine Ogurtsova

Dr. Ogurtsova is working in the Institute of Occupational and Social Medicine, in the working group of Environmental Epidemiology, at University Clinic in the Heinrich Heine University. Her primary qualification includes statistical methods in medicine, epidemiology, and public health with the main focus on R-programming and methodological issues.

2. Dr. Ralf Schäfer

Dr. Schäfer is a psychologist and a head of Psychological laboratory at Clinical Institute for Psychosomatic Medicine and Psychotherapy at University Clinic in the Heinrich Heine University. Dr. Schäfer’s research interest are psycho-physiological questions related to processing emotions and an investigation into the effectiveness of special psychotherapeutic therapies such as the effects of stress management training.

Audience Doctoral students in medicine (Members of medRSD),
Supervisors and Postdocs,
Scientific researchers
Language English, German
Credits medRSD Core competencies
Credits PhD Programme Basic or Cluster Curriculum
Capacity 13
Costs 650 € for External Participants,
Free for doctoral researchers and research associates at the Faculty of Medicine of HHU