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