This advanced course will guide participants towards a reproducible research workflow supported by R. It will provide participants with advanced knowledge how to prepare their data and analyses so that other researchers can understand (and eventually reproduce) how figures and statistical tests were created stepwise from the raw data. We will use R (and RStudio) as interpreted programming language. The course will blend on-line lessons on DataCamp and custom made exercises with weekly 1.5 h hands on sessions. We recommend knowledge of R and RStudio, Markdown and notebooks as can be acquired through our introductory course. This course is generously supported by data camp by providing free access to online learning material for R for our course.
- comprehend the importance of reproducible research.
- learn data analysis in R through the tidy approach.
- be able to create data visualisation via ggplot2.
- understand the process towards a fully reproducible analysis notebook.
- receive an introduction to linear models Be able to do Preregistration and understand registered reports.
- learn how to write a data management plan and receive information on open data repositories.
- understand the usefulness of metadata.
- receive an introduction to open access publishing models contrasted with traditional models.
Dr. Ulf Tölch|QUEST Center for Transforming Biomedical Research, Berlin Institute of Health
Meggie Danziger|QUEST Center for Transforming Biomedical Research, Berlin Institute of Health