Deutsche Vereinigung für Politikwissenschaft
03.08. - 07.08.2020

GESIS Training – Course 2: Introduction to R for Data Analysis, Online via Zoom

Course 2: Introduction to R for Data Analysis

Lecturer(s):

Dr. Stefan Jünger, Dr. Johannes Breuer


Date: 03.08 - 07.08.2020

Location: Online via Zoom

 

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.

A detailed syllabus for this course is available for download here.

 

Keywords

R, data wrangling, exploratory data analysis, data visualization, data analysis

 

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 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.