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Statistical models with R

Course description


Basic skills in programming with R (can be obtained in the Introduction to R course).
Knowledge in statistics especially hypothesis testing and linear regression.

Course overview:

This introductory course describes some basic statistical methods and their application in the statistical software R. Participants will learn how to start applying statistical methods using R and how to interpret the R output. This course requires previous knowledge of statistical theory.


The course covers the application of the following statistical methods in R:

  • Descriptive statistics
  • Hypothesis testing
    • T-test
    • Wilcoxon-test
    • ANOVA and pairwise tests
  • Linear regression

This is not a classical statistics course, but a programming course. In case you are interested in learning when to apply which method or the relationship between different statistical models, we recommend the course Introduction to Statistics.

Moreover, this is not a beginner’s course in R programming. You are expected to have some basic skills in R (as taught in the Introduction to R course)

A graphical explanation of the differences between the courses is given here.


  • We first briefly describe the statistical theory behind the methods and their application in R. We then provide hands-on examples with best-practice solutions.


  • Duration: 1 Day
  • Language: English
  • This course will be offered either on campus (in person), or online.
  • For online courses we use the software Zoom.

Dates and Application:

  • This course is currently not part of the HR Development program at Helmholtz Munich. Employees of Helmholtz Munich can either participate in the four-day version of this course (Introduction to Statistics), or in the courses we provide via HIDA (see below).
  • Courses provided for HIDA:
    • You can check the current dates and whether the courses are already fully booked here.
    • Registrations for these courses are exclusively possible via the provided homepage