GESIS Training Courses
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Scientific Coordination

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

Administrative Coordination

Angelika Ruf
Tel: +49 221 47694-162

Course 3: Introduction to R for Data Analysis

About
Location:
Online via Zoom
General Topics:
Course Level:
Format:
Software used:
Duration:
Language:
Fees:
Students: 400 €
Academics: 600 €
Commercial: 1200 €
Keywords
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Lecturer(s): Dr. Johannes Breuer, Dr. Stefan Jünger

About the lecturer - Dr. Johannes Breuer

About the lecturer - Dr. Stefan Jünger

Course description

[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.


Target group

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


Learning objectives

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.


    Prerequisites

  • prior experience with quantitative data analysis, basic statistics, and regression
  • 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.


    Recommended readings