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Verena Kunz

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Noemi Hartung
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Introduction to R for Quantitative Social Science

About
Location:
Online via Zoom
 
General Topics:
Data Analysis
Course Level:
Beginner
Format:
Workshop
Software used:
R
Duration:
3 days
Language:
English
Fees:
Students: 330 €
Academics: 495 €
Commercial: 990 €
 
Keywords
Additional links
Lecturer(s): Ranjit Konrad Singh, Björn Rohr

About the lecturer - Ranjit Konrad Singh

About the lecturer - Björn Rohr

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 working with R far more comfortable and the scripts more accessible. Moreover, we will use Quarto to generate professional and reproducible 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 toward more open, reproducible, and robust research in R.


Target group

Participants will find the course useful if they want to use R for quantitative research, 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

By the end of the course, 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.
 
Organizational structure of the course
The course will vary between presenting the theoretic functionalities of R, followed by practical demonstration of R-Code and hands-on exercises.
 
  • Participants shall use the learned R functions and packages by individually working on assignments, solving problems typical to quantitative social sciences.
  • Lecturers will be available for individual consultations on participants' projects, to support work on assignments in R, and to facilitate discussions within group work assignments.


    • 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.
    •  
    Software requirements
    R and RStudio will be used in this course. Various packages will be installed during the course, so it is advisable that you make sure that your IT department grants you the necessary rights to install packages from within R. R and RStudio should be installed before the course. We will send you a guide on how to do that a week before the course.


    Schedule

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