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.
This course consists of the following activities:
- Practicals with exercises;
- Participants’ presentations and
The course will take place from 15 Oct to 25 Oct 2019 and be given from 9am to 17 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.
| Session 1
| Session 2
| Session 3
| Session 4
| Session 5
| Session 6
| Session 7
| Session 8
| Session 9
Target group and assumed prior knowledge
The target group of this course are PhD students 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.
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
Participants will not receive a grade, but a qualitative assessment of whether they passed the course. Both members of a group will receive the same assessment. Sheets detailing the assignments will be distributed during the course. The solutions to assignments 2 to 4 need to be completed and submitted by 31 Oct 2019 by each group by email to email@example.com. For assignment 1, each group needs to prepare a short presentation (details will be given on day 1). Participants receive 4 ECTS for successfully passing this course.
| WGS PhDs with TSP
| Other PhDs, postdocs and academic staff
| Participants from the private sector
The course fee includes coffee/tea and lunches
Participants can cancel their registration free of charge 1 month before the course starts. A cancellation fee of 100% applies if a participant cancels his/her registration less than 1 month prior to the start of the course.
The organisers have the right to cancel the course no later than one month before the planned course start date in the case that the number of registrations does not reach the minimum.
The participants will be notified of any changes at their e-mail addresses.