RSS001.O1 Crash course in R – a gentle introduction
The guiding logic of the course is to give practical knowledge of the whole data analysis workflow:
- Monday – Getting to know R |Importing data
- Tuesday – Data wrangling/cleaning
- Wednesday – Exploratory analysis
- Thursday – Visualization
- Friday – Analysis | Reporting the results
Reflecting on the realities of typical research projects, the beginning of the course focuses on data cleaning and getting data into a shape which allows us to analyze and visualize it properly. The exploratory analysis and data visualization parts are heavily intertwined.
We will also review how to get various different types of datafiles into R (from Stata, SPSS, Excel).
We will learn how to make descriptive statistics, how to group data, and how to explore a given dataset. The course puts strong emphasis on visualization components and we will learn to use the ggplot2 package to produce wonderful looking graphs.
While this is a general R intro, we will look into how to carry out some of the most common analysis in R (hypothesis testing, linear regressions) and how to get that output into a nicely formatted academic paper. RMarkdown provides an intuitive workflow that allows us to export the final results to a Word file, a pdf, or html.
|12 June 2023 - 16 June 2023|
Early Bird Regular: €504 (application deadline* April 1st)
|Scholarships and discounts||
Please note that Erasmus+ scholarships are not possible for this course
*Your application is only completed when the course fee has been paid
|Course leader||Akos Mate|
|Level of participant||
|Admission requirements||There are no requirements for this course, other than to have a laptop capable of running R (basically anything made after 1998).|
|Mode of Study||Online|
|ECTS||1 Find more information here|