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Reproducible Research with R
Description
This course will guide participants towards a reproducible research workflow supported by R. It will provide participants with knowledge on 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 four 4 h hands-on sessions.
This course is generously supported by DataCamp by providing free access to online learning material for R for our course.
Learning goals
- 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
Main lecturer
Ulf Tölch, Research group leader an project team leader "Education, Training & Quality in Research"
Anja Collazo, PhD Candidate - DECIDE
Prerequisites
Some experience with R is necessary. This can be acquired by completing the two DataCamp courses: Introduction to R and Intermediate R. DataCamp access will likely be available starting 1st of April 2023.
Certificates
A certificate will be provided. ECTS: 2,0
Important information
Dates: tba
Time: tba
Course language: English
Location: Conference room Domblick, 5. floor, BIH im Spreepalais, Anna-Lousia-Karsch-Str. 2, 10178 Berlin
Registration:
We have reached the maximum number of participants. If you want to sign up for the waiting list for the course in the next winter semester 2023/2024, please register here.