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Introduction to R

About
Location:
Online via Zoom
 
General Topics:
Data Analysis
Course Level:
Beginner
Format:
Workshop
Software used:
R; RStudio
Duration:
1-3 days
Language:
English
Fees:
Students: 300 €
Academics: 450 €
Commercial: 900 €
 
Keywords
Additional links
Lecturer(s): Daniel Wagner, Judith Gilsbach

About the lecturer - Daniel Wagner

About the lecturer - Judith Gilsbach

Course description

R is a versatile and powerful statistical programming language with rising importance in the social science community. It is free of charge and numerous additional and freely available packages, which expand its functionality to a wide range of applications.
This workshop gives an introduction to the statistical programming language R. It is targeted at social scientists with no, or very little prior knowledge of R. No advanced statistics skills are needed to participate, but some statistical knowledge (e.g. of linear regression) is beneficial to follow the examples.
All coursework will be done using the programming language R and the environment RStudio. Participants are kindly asked to install both on their machines beforehand. A manual on how to do this will be provided in advance. This will save us time during the class. If you have trouble installing the software, please do not hesitate to contact the lecturer before the course starts or ask during the course.
The course will start with an introduction to what packages and functions are and how to load the data into R. We will go on with data wrangling, mainly using a package collection called “tidyverse”. The course will also cover basic regression models, visualization of data, and the preparation of clean documentation in R Markdown. There will also be some time for specific demands of the participants. Each unit will consist of an introduction by the lecturer, followed by hands-on exercises.
The lecturer will use a Windows system. Guides for Mac and Linux users can be found online. Especially for the latter, it is not guaranteed that the replication of all exercises will be entirely possible. Linux users should acquaint themselves with the possible challenges; the lecturer will assist to the degree that it is possible.


Target group

Participants will find the course useful if:
  • They are researchers who look for an interactive introduction to using R to import, manage, transform, explore, analyze, and visualize data
  • They have no or little experience with R
  • They are students who have completed some first lectures on statistics


    • Learning objectives

    By the end of the course participants will:
  • know how to import, manage, transform, visualize, and analyze data
  • be able to apply their new skills to their own research projects
  • have some basic understanding of R Markdown
  • know how to help themselves in the internet for tackling more advanced questions and programming tasks


    • Prerequisites

  • Basic understanding of statistics, e.g., know what a regression analysis is
  • Experience with other statistical software (e.g., Stata, SPSS or SAS) is helpful but not necessary
    •  
    Software requirements
    Please install the latest versions of R and RStudio:
    You can download R for free here: https://cran.r-project.org/bin/windows/base/ (and yes, the page looks odd, but it is the correct one).
    You can download the free version of RStudio here: https://posit.co/downloads/.
    Please also make sure that you have a program installed that can display HTML Documents; for example a web browser like Firefox, Chrome, or Edge would suffice.
     
    If you have problems with the technical setup, we will tackle them in the first session of the course.


    Schedule

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