Course 3: Introduction to Data Analysis Using R

Lecturers: Dr. Jan-Philipp Kolb, Alexander Murray-Watters

Date: 6-10 August 2018
Time: 09:00-13:00, 14:00-16:00

Short Course Description:

The open source software package R is free of charge and offers standard data analysis procedures as well as a comprehensive repertoire of highly specialized processes and procedures, even for complex applications. Emphasis in this course will be on methods of graphically-based data analysis as R is particularly suitable for it.

Course Prerequisites:

  • Prior experience with data analysis, basic statistics, and regression.
  • As we will work with GESIS Panel data, it would be good to download the campus file of the GESIS Panel (
  • Basic familiarity with the use of a computer.

    Target Group:

    • This course is for people that work with survey data and want to use R as an additional tool.
    • The participants should have already attended an introductory event in statistics. Experience in dealing with other statistics packages is helpful, but not a requirement.

      Course and Learning Objectives:

      Our workshop provides a hands-on introduction to R and lays the foundations for independently developing your skills in dealing with the programming language R. The participants can expect to receive an overview of the functional scope of R, master the import and export of data, and how to perform basic data analysis in R.

      Organizational Structure of the Course:

      The best way to learn R is to try things out and apply the presented concepts. Therefore, we will have a mixture of classroom instruction (about three hours per day), hands-on exercises/lab sessions (about two hours per day) and contact time for individual consultations on participants’ projects.

      Software and Hardware Requirements:

      Course participants will need to bring a personal laptop in order to do the hands on exercises. Ideally, the laptop already has R ( and Rstudio installed ( Both programs are free and open source.