This course is not an ordinary course where the teacher follows a prescribed curriculum. It is rather a course where you own your own learning (yoyol).
In this course, yoyol means that you will learn a lot from your peers, by giving and receiving feedback, and by sharing your knowledge that you aquire by own research and reading. It also means that you have some influence on the contents by chosing some of the topics we are going to deal with.
The course will start rather traditionally, with topics around
As the course proceeds, teaching is more and more overtaken by yourself and your peers. You will present topics to each other and include small exercises. In addition to the above mentioned topics, you will also introduce
There will be about four home programming assignments in the first half of the course, and you will give feedback to each other on these exercises.
In the second part of the course you will spend time mainly on creating your own R package in a team. This part of the course simulates open source software development as is common in the R community. The aim is to produce a presentable piece of software that you can be proud of, and that documents your skills in coding, communication and collaboration.
You start by defining the purpose of your package. It is very popular to centre this around topics from statistics courses you have or have had, but there is also a list of suggestions to pick from. You will then organize, schedule, and not least also take hands on the work of your team, which includes both programming, code testing, and writing documentation. You will provide feedback and sparring to another team during the development process. Finally, you will even set up a web page for your package.
We will pobably use the messaging program "Slack" (or a similar alternative) to communicate course announcements and share files, code snippets and wisdom. Slack is particularly popular with software developers in industry.
If the above description sounds exciting to you, you will probably enjoy the course 😃.
I assume that you have a minimum of experience with R. You have dealt with vectors, lists, matrices and data frames, and have written a simple function before, or have used for-loops. If you do not meet these prerequisites, please contact the course responsible (Ute Hahn) before enrolling. You can check your knowledge concerning basic data types in this selftest, where you also get links to a free online course to catch up.
You will probably enjoy the course less, if
This course is designed with students of statistics in mind. Therefore, the examples dealt with in the course, as well as the subjects of your packages, are mostly from the field of statistics. The course can also be useful for students of similar subjects, such as math-economy, or bioinfomatics, who have a good background in statistics.
The course's concepts and special "workshop" character are not doable if the class is too large or too small. Therefore, admission is limited to twelve, but on the other hand, the course will not be run for less than six students.
If for some reason more than twelve students are admitted, the course's plan needs to be changed, in particular concerning allocation and number of student topics. In 2019, seventeen students were admitted. As a consequence, student presentations had to be done also during the project phase.