Statistics for Experimental Life Scientists
The course teaches principles of statistical analysis as required for typical experiments in preclinical biomedical research, i.e. with a focus on considerations related to small sample sizes. This compact workshop is largely based on examples from the work of the participants. Moreover, each participant is supposed to supply a dataset based on own research along with a data analysis question. It is expected that 20-30% of total course will be based on discussing these examples from the participants. While many useful software packages exist, the course will be based on using GraphPad Prism. Participants not having access to this software will get a free temporary license as part of attending the course.
- Why do I need statistics?
- Describing data
- Fundamental concepts
- What do P-values mean?
- Choosing a statistical test
- Statistical analysis of multiple groups
- Correlation, regression and curve fitting
- Statistical power
- How to report statistical results
- Design of robust studies
Target audience: Doctoral candidates, postdocs and clinician scientists
Maximum number of participants: 15
Please read the texts you receive before and bring your dataset based on own research along with a data analysis question to the workshop.
Next workshop: to be announced
Technology: MS TEAMS
Please check that your PC meets the requirements beforehand (microphone, camera, Internet connection).
For the workshop, 2.5 CP for scientific skills training can be credited.