Nach meinen drei vorigen Beiträgen zu RWordPress nun ein weiteres Beispiel, wie Digitalisierung Forschungsprozesse transformieren kann. Der Beitrag zeigt wie sich in derProgrammiersprache R – mit der Hilfe einiger Erweiterungen – nicht nur Daten (statistisch) verarbeiten lassen, sondern Kommentare als auch die Interpretation in einem Arbeitsprozess publiziert werden kann. Die damit verbundene Strategie heißt Literate Programming und bedeutet, dass Dokumentation als auch der Quelltext des Programms in einer gemeinsamen Datei zugänglich sind.
This is another follow-up article from previous posts Publishing R Statistics directly into WordPress and imgur.com website. This is very important because otherwise the transfer to WordPress would encrypt the pictures to an awful peace of code. An example how this looks can be seen from my first trial.
This is the follow-up article from the previous post Publishing R Statistics directly into WordPress. This time I will explain in more detail how to apply the different packages. There is a companion webpage where you can see the content of the different program chunks. You will see how to post text, graphic, uploading files, setting categories and tags, fill in the excerpt and providing a thumbnail.
In contrast to the previous post I have now establised the facility to upload graphics resulted from R calculation automatically to the imgur.com website. This is very important because otherwise the transfer to WordPress would encrypt the pictures to an awful peace of code. An example how this looks can be seen from my first trial.
In the first episode about my personal learning experiences, I criticized that rigid curricula are not adequate to support experienced learner. This second episode is a follow up of this thought. I discuss the subject in more detail and in a more general way addressing not only R programming and data science but generally all adult learners who have work experiences and want to improve their knowledge and skills in their respective field of expertise. I will also present a model how self-determined learners could better be supported.
This is the first report of a series of personal experiences in learning the statistical programming language R to acquire competencies of a data scientist. In this kick-off article, I will present an example, why cohort learning in the age of individualisation is not appropriate anymore. I will suggest an alternative, present my earned certificates and explain why I interrupted (or aborted?) a nine-course introduction to data science taught by professors of John Hopkins University and offered via the MOOC-platform Coursera.