Statistical data analysis in R
The workshop covers a basic introduction to statistical analyses of quantitative data in R and will help participants in developing analysis workflows using the editor/IDE RStudio.
The software/programming language R is one of the most commonly used tools to perform statistical analyses. It is free to use and features a vital community of researchers developing software packages within R to facilitate state-of-the-art analyses in many fields.
The first day of the workshop comprises two topics: a short introduction/refresher to basic concepts of statistical analyses as well as an introduction to the implementation of data analysis methods in R. We will take a look at the most important features of RStudio, learn how to read and write datasets and get to know the most important methods to recode, filter and manipulate statistical variables.
Statistical concepts covered will include uni- and bivariate descriptive analyses, statistical tests, and multivariate regression models. You will learn to tabulate data, to calculate and test common correlation estimates and statistical models, and to produce publication-ready tables and plots to communicate your results. All analyses presented will be practised in hands-on sessions with real-life datasets.
After one week to apply the techniques to your own data, the second day of the workshop will give us the opportunity to discuss all questions and obstacles that come along with your own research applications. Here, we’ll also have time to talk about more „specialised“ topics you might need to adress your individual research questions.
The workshop is primarily aimed at doctoral researchers in the humanities and social sciences. Prior statistical knowledge is not required, though a basic understanding of statistical concepts is recommended – the coverage will be necessarily dense.
The registration form can be accessed from this page.
10:00 bis 17:00 Uhr
09:00 bis 12:00 Uhr
Bitte melden Sie sich direkt beim Veranstalter für die Veranstaltung an.