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Scientific Coordination

Verena Kunz

Administrative Coordination

Claudia O'Donovan-Bellante
Tel: +49 621 1246-221

Introduction to R

About
Location:
Online via Zoom
General Topics
Data Analysis
Course Level
Format
Software used
Duration
Language
Fees
Students: 300 €
Academics: 450 €
Commercial: 900 €
 
Keywords
Additional links
Lecturer(s): Matthias Roth, Lukas Birkenmaier

About the lecturer - Matthias Roth

About the lecturer - Lukas Birkenmaier

Course description

R is a powerful, versatile, and open-source software environment for statistical computing. With R, it is possible to manage and transform data, perform a plethora of statistical analyses, and visualize scientific results. However, using R for the first time can be daunting. R is a programming language and thus works differently than many commercial statistical software packages that primarily use graphical user interfaces (e.g., SPSS, Excel).  
In this three-day workshop, we will introduce R to researchers with no or very little prior experience with R.
  
We will start with the very basics, installing R and the popular development environment R Studio. Having R up and running, we will take a slow-paced approach explaining the fundamentals of R usage: First, we will cover basic but important R programming concepts. Second, we will focus on how to use R Studio.  Third, we will show how you can extend R's capabilities to perform analyses using R packages. Fourth, we introduce the popular R package “tidyverse”, which you can use to perform the most common data wrangling tasks: Reading-in, sub-setting and transforming data from various data sources. Finally, fifth, we will use the "tidyverse” to do basic exploratory data analysis and visualisations. 
  
The exercises you complete during the course provide you with reference material for common R programming tasks. Additionally, focus is given to the usage of online resources to find answers to programming problems.  
  
At the end of the course, you will know the fundamentals of R. In particular, you will be able to work with tabular data, such as reading in, transforming, and analyzing data in R. Furthermore, we aim to provide you with all the tools and resources to further advance your R skills on your own. 


Target group

Participants will find the course useful if:
  • They are new to the R language
  • Want to get a practical introduction to R and RStudio
  • Want to use R to import, manage, transform, explore, analyze, and visualize data
  • Would like to learn R in an open and cooperative environment, where questions and explicitly encouraged


  • Learning objectives

    By the end of the course participants will:
  • Be familiar with setting up and using R and RStudio on their computer
  • Have a basic understanding of fundamental programming concepts and their application in R  
  • Be able to perform basic data wrangling tasks using the “tidyverse”
  • Be able to interpret error messages and find answers online
  •  
    Organisational Structure of the Course:
    The organizational structure of the course is specifically designed to provide participants with enough resources to get to know and explore the R environment. The interactive workshop comprises of a mix of short lecture-style input sessions followed by corresponding practical lab sessions. Each topic will first shortly be introduced by the instructors. Afterwards, participants will be provided with a set of exercises on each specific topic. We are going to discuss the solutions together in class before the start of the next input session.
    Throughout the seminar, both instructors will be available for consultations as well as practical advice.


    Prerequisites

  • A basic understanding of social science research
  •  
    Software requirements:
  • Participants will be requested to download R and RStudio in advance. However, a detailed instruction will be sent beforehand via e-mail, and there will be points of contact available for troubleshooting.


  • Schedule

    Recommended readings