In the open science movement, research data is expected to be as open as possible and as closed as necessary. But what does this mean in practice, especially when dealing with patents, personal data or other sensitive information? This lecture will present the principles of open and FAIR data, research data management and the legal, ethical and institutional frameworks that govern data sharing. Participants will gain an overview of researchers’ rights and obligations and funders’ requirements, as well as guidance on data repositories.

In this Basic Statistics Course you will learn the basics of statistical data analysis for your research projects. The course is application based and will empower you to improve your study planning and get more confident with your statistical analysis.

It contains the following topics:
Design of experiments / study design
Data collection and entry
Structure of statistical analysis
Significance tests
Choosing the appropriate statistical method
Paired and unpaired data
Level of measurement / variable type
Checking of assumptions and normality
Effect size measures
Sample size calculation and power analysis

The course is organized with self-learning material (short videos, handout and exercises) and two live and online Q&A sessions. After a short kick-off meeting you watch the videos and do the exercises at your own pace. During this time, you can pose your questions in a chat. Within an interval of one week we meet for two Q&A sessions online, where you can ask questions concerning the topics or your own projects.

The course runs for just over two weeks. Plan approx. 2.5 hours per week for independent work with the materials plus the time for the meetings (30 minutes kick-off and 2x 45 minutes Q&A session).

Valeria Heimann studied mathematics and completed her PhD at Heidelberg University. She has been with d-fine since 2016, working at the interface of business expertise, processes, and IT. In various projects, she has supported companies in making complex structures clearer, more efficient, and more sustainable. Her current content focus lies in the areas of processes and Enterprise Architecture. Parallel to her work at d-fine, she studied Software Engineering with a focus on Project Management at the University of Oxford. These studies were supported and promoted by d-fine. For about half a year, she has additionally been responsible for the sales and marketing activities of a non-profit data platform sponsored by d-fine, where she drives its strategic further development.