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.​