Introduction to R

Doctoral course within the doctoral programme in Epidemiology

Course number: 2958

Credit points: 1,5

Course dates: May 28-31 + June 1, 2018

Application period: 16th October - 15th November, 2017

To application



The purpose of this course is to introduce students to using the R statistical software to perform basic to intermediate statistical data analysis in a replicable manner.

Learning outcome

After successfully completing this course, students are expected to be able to:

  • explain basic concepts of the R language and environment, the online- and offline sources of documentation for R, and basic concepts of data management and workflow in a standard statistical analysis,
  • run a standard statistical analysis interactively within the R environment,
  • formalize and document such a standard analysis as a stand-alone R script,
  • produce graphical representations, as part of reporting their analysis,
  • interpret their scripts for potential simplifications via functional implementation,
  • find, install and compare extension packages for unfamiliar statistical application


The course will cover the basic elements of a standard statistical workflow: reading data into R; pre-processing and quality assessment of data via numerical and graphical methods; descriptive statistics via summary measures, tabulations and graphics; basic statistical inference in terms of significance testing and confidence intervals; specification, fitting & diagnosis of regression models; exporting and reporting results from the previous steps.

The course includes an introduction to the Rstudio integrated development environment to provide a common framework for interactive and scripted analysis. The extensibility of the R system will be demonstrated by example.

Course director

Senior researcher

Alexander Ploner

Phone: +46-(0)8-524 823 29
Organizational unit: Department of Medical Epidemiology and Biostatistics (MEB), C8

Contact person

Educational administrator

Gunilla Nilsson Roos

Phone: +46-(0)8-524 822 93