Core Statistics using R (ONLINE LIVE TRAINING)
Organizer: University of Cambridge
Host institution: University of Cambridge Bioinformatics Training
Start: Wednesday, 16 March 2022 @ 09:30
End: Wednesday, 30 March 2022 @ 16:30
Venue: Craik-Marshall Building
Country: United Kingdom
Postcode: CB2 3ARTarget audience:
- Graduate students
- Postdocs and Staff members from the University of Cambridge
- Institutions and other external Institutions or individuals
- This course is included as part of several DTP and MPhil programmes
- as well as other departmental training within the University of Cambridge (potentially under a different name) so participants who have attended statistics training elsewhere should check before applying.
The Bioinformatics Team are presently teaching this course live online, with tutors available to help you throughout if have any questions. We continue to monitor advice from the UK government and the University of Cambridge on resuming in-person teaching in our training room.
This award winning virtually delivered course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.
There are three core goals for this course:
Use R confidently for statistics and data analysis
Be able to analyse datasets using standard statistical techniques
Know which tests are and are not appropriate
R is an open source programming language so all of the software we will use in the course is free.
In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.
After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.
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