GESIS Training Courses
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Wiss. Koordination

Dr.
Sebastian E. Wenz
Tel: +49 221 47694-159

Administrative Koordination

Angelika Ruf
Tel: +49 221 47694-162

Course 2: Introduction to R for Data Analysis

Dozent(en):
Dr. Stefan Jünger, Dr. Johannes Breuer

Datum: 03.08 - 07.08.2020 ics-Datei

Veranstaltungsort: Online via Zoom

Referenteninformationen - Dr. Stefan Jünger

Referenteninformationen - Dr. Johannes Breuer

Seminarinhalt

[This is a 24 hour class.]
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. In addition to providing an introduction to the basic concepts and functionalities of R, we will go through a prototypical data analysis workflow in the course: import, wrangling, exploration, (basic) analysis, reporting.
A detailed syllabus for this course is available for download here.


Keywords



Zielgruppe

Participants will find the course useful if they want to use R to wrangle, explore, visualize and analyse their data.


Lernziel

By the end of the course participants will:
 
  • Be comfortable with using R and RStudio
  • Be able to import, wrangle, and explore their data with R
  • Be able to conduct basic visualizations and analyses of their data with 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 lectures and hands-on exercises. More specifically, each topic will be introduced in a lecture by the instructors. Participants will then receive a set of exercises on each topic that they work on alone. The solution of the exercises will then be discussed before the start of the next lecture part.


    Voraussetzungen

  • prior experience with data analysis, basic statistics, and regression;
  • basic familiarity with the use of a computer
  • experience with using other statistical packages (e.g., SPSS or Stata) is helpful, but not a requirement.
  •  
    Software and Hardware Requirements
    Course participants will need a computer or laptop with R (https://cran.r-project.org/) and Rstudio installed (https://www.rstudio.com/). Both programs are free and open source.


    Literaturempfehlungen