Offered by the Professorship of Public Health and Prevention at TUM.
Welcome to our Self-Study R Course (SSRC)!
The purpose of the SSRC is to teach participants basic R programming skills from scratch.
The SSRC is comprised of 8 chapters that build upon each other.
Completing all chapters requires a time investment of about 30 hours. Since the SSRC is a pure self-study course, participants are free to decide when to make this time investment.
Participants who complete the whole course will be rewarded with a solid foundation of R programming skills. Furthermore, they will learn how to navigate through the R and R Studio universe. They will learn how to learn new methods and commands by themselves, which is by far the most important skill for anybody who is working with R or any other programming language.
For more details about the SSRC please check out the Course Introduction.
The SSRC is designed for everybody who wants to acquire basic R programming skills in a structured way and in a reasonable amount of time.
No prior knowledge in R or any other programming language is required. We assume participants to know some very basic statistics concepts, though. To learn more about these requirements, please check out the “Prior Knowledge” section of the Course Introduction.
The SSRC has been developed by the Professorship of Public Health and Prevention at TUM. The goal of our interdisciplinary team is to generate and synthesize scientific evidence to support decision making in health systems and health policy, with the ultimate goal of improving population health.
We are teaching several modules in our departments Master’s program. In two of these modules, students have to analyze data in R to meet the learning objectives of the respective modules.
When we started teaching in the Master’s program in 2020/2021, we learned that the academic background of students and hence also their prior knowledge in statistics and R are very diverse. There was no doubt that we have to bring all students on a certain R skill level before the programming parts of our modules can start. After intense discussions on how to teach the required R skills, we decided to offer a voluntary self-study R course accompanied by a series of Q&A sessions in the beginning of the semester. We decided to go with a self-study course for two reasons. Firstly, a self-study course enables students to learn at their own pace. This lets us account for the heterogeneity of students in our Master’s program. Secondly, a self-study course gives students some discretion on when to do the course. This lets us account for the fact that students in our Master’s program have very diverse schedules. So far, our experiences with the self-study format have been quite good and our students also seem to appreciate the self-study nature of the course.
The SSRC has been initially developed in the winter term of 2021/22. In the same term it has been offered to students for the very first time. In the summer term 2022 it has been offered for the second time. In the first two terms, the SSRC website did not exist yet. Instead the material was available in the university teaching file system. However, this way of presentation neither was convenient for lecturers nor for students. Hence, we decided to create this website to organize and offer the SSRC from the winter term 2022/2023 on. Based on the feedback we received from students who did the SSRC since then, we revised the website multiple times.
The SSRC itself benefits tremendously from the R community. Actually, the course would not work at all without the content provided by the community members. In return, we decided to make the SSRC publicly available and (of course) also free of charge.
If you like the SSRC and the idea behind it, you can help us to raise the awareness of it by twittering something positive a about the SSRC and/or by spreading the word among your peers and people who might be interested in the SSRC.
In the past, the SSRC heavily benefited from the feedback of the students doing the course. Thank you very much to all of you!
But for sure the SSRC is not perfect yet and there is still a lot of room for improvements. Hence, we are very happy about any constructive feedback. Just send an e-mail with the subject “SSRC” to info.php@mh.tum.de.
Professorship of Public Health and Prevention
Department for Sport and Health Sciences
Technical University of Munich
Homepage: Professorship of Public Health and Prevention
E-Mail: info.php@mh.tum.de
Twitter: TUMPublicHealth