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Scientific Coordination

Verena Kunz

Administrative Coordination

Noemi Hartung

Introduction to R

About
Location:
Online via Zoom
 
General Topics:
Course Level:
Format:
Software used:
Duration:
Language:
Fees:
Students: 330 €
Academics: 495 €
Commercial: 990 €
 
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Lecturer(s): Christian Pipal, Isabella Rebasso

About the lecturer - Christian Pipal

About the lecturer - Isabella Rebasso

Course description

R is a powerful, versatile, and open-source software environment tailored for statistical computing. It enables users to efficiently manage, manipulate, and analyze data, offering diverse options for presenting scientific results. Despite its capabilities, beginners may find R challenging due to its programming language structure, which differs significantly from commercially available statistical software like SPSS or Excel and their graphical user interfaces.
This four-day workshop addresses researchers who have little to no prior experience with R. We will start by introducing R and the popular development environment RStudio. We will move at a slow pace, using real-world data analysis examples. We will walk through the typical steps of analyzing data, while learning the fundamental concepts of R and the popular R package “tidyverse”.  A significant focus during this workshop will be on the “tidyverse”, now a standard toolkit for data wrangling tasks in R, including data importing, sub-setting, and transformation from various sources. After introducing each new set of tools, we will revisit underlying R programming concepts, such as data types, functions, and control structures. We will also explore how to enhance R's capabilities using additional R packages. Finally, we will introduce participants to basic data modelling, and use the "tidyverse" package to conduct basic exploratory data analysis and visualizations.
Throughout the workshop, participants will complete exercises that provide them with reference material for common R programming tasks. Each afternoon is dedicated to applying the techniques discussed in the morning, as well as more advanced coding challenges. By the end of the course, participants will have a solid understanding of the fundamentals of data analysis with R (reading in and saving data, transforming data, and analyzing data). Overall, this course equips participants with all the tools and resources necessary to continue advancing their R skills on their own.
 
Organizational structure of the course
The course's structure aims to equip participants with ample resources to acquaint themselves with the R environment. The workshop is interactive and incorporates brief lectures on various topics, followed by afternoon practice sessions. These practice sessions will be flexible, allowing participants to work at their own pace and focus on their personal learning goals. Throughout the seminar, both instructors will be available to offer support, answer questions, and share practical tips to help you get the most out of the experience.
 


Target group

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


Learning objectives

By the end of the course you 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 visualize data using “ggplot2”.
  • be able to interpret error messages and find answers online.


Prerequisites

A basic understanding of quantitative social science and hypothesis testing, including introductory statistics (e.g., distributions, t-tests, cross tables, and linear regression).  
 
Software requirements
You will be requested to download R and RStudio in advance. You will receive detailed instructions beforehand via e-mail, and there will be points of contact available for troubleshooting. There will also be a dedicated space for installation troubleshooting during the first workshop day.


Schedule

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