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Crash Course in R – A Gentle Introduction (RSS00.06) - Confirmed

This one-week online course covers the basics of programming in R: importing and exporting data; transformation, cleaning, analysis, and visualisation of data; producing publication-ready, quality graphs and tables to report your results; iterating certain workflows; as well as working in RMarkdown, which allows you to generate an entire research paper with RStudio.

 

    General

     

    The application deadline has passed, applying is no longer possible

    This crash course covers all aspects of conducting quantitative research. You will learn how to import data, how to perform the necessary data cleaning and transformation steps, create subsets or merge your dataset with other external sources of data. Some of these steps might be a bit different depending on the type of data you intend to work with (numeric, character, categorical, date, etc.), but the course discusses these differences and shows examples of working with all of them. Knowing that some of you will come with some experience with other statistical software, we cover how to import and export data to proprietary (STATA, SPSS, etc.) formats. 

    The course does not cover statistical theory, but it will go through some applied tools for data analysis and hypothesis testing, such as comparing groups and regressions. Topics (and skills) of data visualisation form an inherent part of this course: relying on ggplot2, you will create scatterplots, illustrate temporal trends, present distributions in intuitive ways and express regression results concisely with coefficient plots. 

    A separate session is dedicated to using RMarkdown, an essential workflow allowing you to generate an entire research paper or report (as an HTML, PDF or Word file). Following a learning-by-doing approach, you will have a chance to solve coding exercises both in teams (in breakout rooms) and alone, and to test your newly acquired knowledge via assignments between sessions.

    After successful completion of this course you will be able to import and export data to/from R, conduct simple statistical analyses using R, visualize data, presenting patterns effectively and consicely, and transform, recode, label, merge and subset data in R. 

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    Cannot join us this year? 

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    Starting date

    10 June 2024, 9 am
    Educational method
    Online
    Main Language
    English
    Sessions
    10 June 2024, 9 am - 14 June 2024, 5 pm
    Teacher(s)
    Daniel Kovarek
    Unique code
    RSS00.06

    Factsheet

    Type of education
    Course
    Entry requirements
    None
    Study load (ECTS)
    1
    Result
    Certificate
    Organisation
    Radboud Summer School

    Online Course

    This online course covers all aspects of conducting quantitative research with R. You will learn how to:

    • import data into and export data from R; 
    • perform simple statistical analysis using R; 
    • visualise data; 
    • present patterns effectively and consistently;
    • transform, recode, label, merge and subset data in R.

    Online course

    This is an online course, which means that unfortunately the social activities of the Radboud Summer School do not apply to this course. In addition, the program will also differ from the weekly schedule published on the website. 

    Two weeks before the course starts you will be added to our online platform Brightspace, where the new times will be communicated.

    Daniel Kovarek

    Daniel Kovarek

    Daniel Kovarek is a Research Fellow at the European University Institute, at the Robert Schuman Centre for Advanced Studies. He holds a PhD in Political Science from the Central European University. He studies political behaviour at the voter and the elite level; his expertise lies in the intersection of political geography and distributive politics. Previously, he has been teaching a wide variety of graduate-level courses on quantitative methods, applied statistics, programming, research design, as well as comparative politics. His research has appeared in Research & Politics, The ANNALS of the American Academy of Political and Social Science and Environmental Politics, among others.

     

    The application deadline has passed, applying is no longer possible

     

    Costs

    • Regular: €699 (application deadline 13th of May)
    • Student & PhD's: €466 (application deadline 13th of May)

    Discounts and Scholarships

    Admission

    Level of participant: 

    • Master
    • PhD
    • Postdoc
    • Professional

    Admission requirements: 

    • None

    Admission documents: 

    • None

    Apply for this course