GESIS Training Courses
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Scientific Coordination

André Ernst

Administrative Coordination

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

Introduction to R for quantitative social science (Online-Workshop!)

About
Location:
Online via Zoom
 
General Topics:
Course Level:
Format:
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Duration:
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Fees:
Students: 300 €
Academics: 450 €
Commercial: 900 €
 
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Lecturer(s): Dr. Ranjit Konrad Singh, Dr. Adrian Stanciu

About the lecturer - Dr. Ranjit Konrad Singh

About the lecturer - Dr. Adrian Stanciu

Course description

R is a powerful, versatile, and open software environment for statistical computing and graphics. As open-source software, its functionality is constantly expanded with packages from the active R community. This workshop is intended to smooth your entry into the R universe.
The course will cover everything from setting up R, loading data, preparing data, exploring data, performing basic analyses, and presenting your findings in automatically generated documents with text, tables, and graphics.
We will use the comfortable RStudio environment and packages from the so called “tidyverse”, which makes R far more comfortable and the scripts more accessible. Moreover, we will use R Markdown to generate clear output documents and ggplot2 to generate graphs.
We will draw our examples from survey data: Specifically, the German general social survey, ALLBUS. However, the course can just as easily be applied to other social science data in table form. During the workshop, we will alternate between short input sessions and practical exercises and examples.
At the end of the workshop, you will have a good impression of what R can do for you. You will be able to tackle primary analyses and data exploration. However, most notably, the workshop will start you out on your journey towards more open, reproducible, and robust research in R.


Target group

The workshop addresses quantitative researchers who want to start with R, be that for greater efficiency, more open and reproducible research, or more powerful and complex analyses. We assume that participants have no or only passing experience with R.


Learning objectives

Participants will have a basic understanding of how R works and how to approach common tasks in quantitative research. The course will also illustrate why R is beneficial for collaboration, sharing, and replication of analyses. Lastly, the course forms a sound basis for participants to delve more deeply into more advanced R functionality, such as an in-depth understanding of ggplot2, complex analyses, or task automation.


Prerequisites

Participants should have a basic understanding of quantitative social science research. We also assume that participants are familiar with data in a table format (i.e., organized in variable columns and observation rows). Participants do not require prior experience in R or any other programming language.


Schedule

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