Course
Introduction to programming in R for social sciences - 3 ECTS
This course provides an introduction into programming with the free software R for PhD candidates in social sciences. It teaches participants the logic of the programming language, how to independently and efficiently work with R and to find their own way through the software. For this aim it is designed as a hands-on course with a number of exercises analyzing real data and preparing simple graphs so that participants have sufficient chance to practice their work with R. The course introduces participants to the analysis of numerical, categorical data as well as to quantitative text analysis (text mining).
Lecturers
Learning outcomes
After successful completion of this course participants will:
Understand the structure of R and its basic programming principles;
Have an overview of supporting sources and R graphical capabilities;
Become independent users of R being able to
Carry out data analysis and
Create own functions as well as graphs.
Activities
This course consists of the following activities:
- Lectures;
- Practicals with exercises;
- Participants’ presentations and
- Assignments.
The course will take place from 18 Oct to 22 Oct 2021 and be given from 9am to 18 pm consisting of lectures and practicals. The lectures and demonstrations in the morning present new knowledge. They are followed by practicals in the afternoons giving participants the chance to comprehensively practice the newly acquired knowledge. At the end of each practical all participants jointly discuss and compare individual solutions.
Preliminary schedule
Session 1 | 18-10-2021 | 9.00-18.00 |
Session 2 | 19-10-2021 | 9.00-18.00 |
Session 3 | 20-10-2021 | 9.00-18.00 |
Session 4 | 21-10-2021 | 9.00-18.00 |
Session 5 | 22-10-2021 | 9.00-18.00 |
Target group and assumed prior knowledge
The target group of this course are PhD candidates who write their thesis in any of the social sciences. Participants are ideally in the second, third or fourth year of their PhD having already experience with independent scientific research. Participants have experience in carrying out quantitative data analysis and in practicing of applied research in social sciences and sound knowledge of statistical or econometric foundations of applied quantitative data analysis. They should have extensively worked with data in one or more standard software package such as Excel, SPSS, Gretl etc.. Having experience in using command-line based software (such as Stata or SAS) for statistical analysis or graph creation is an advantage, but no precondition. Attendance of interested post-docs or staff is possible as well.
Assessment
Participants work in groups of 2 persons on the assignments (participants can also choose to submit them individually if they wish). Each group needs to pass the following four assignments for passing the course:
Assigment 1: Presentation
Assigment 2: Tasks in R on data processing and descriptive data analysis
Assigment 3: Tasks in R on numerical analysis
Assigment 4: Tasks in R on quantitative text analysis
Course fees
WGS PhDs with TSP | 300 |
Other PhDs, postdocs and academic staff | 600 |
Participants from the private sector | 900 |
The course fee includes coffee/tea and lunches