ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
Introduction to Statistics and Data Visualisation with R
26 January 2021
26 January 2021
For-profit: 1200 CHF
This course is now full with a waiting list.
This course will be streamed only for the registered participants. Registered participants will receive specific information directly from the respective course’s organizers.Overview
This course is designed to provide researchers in biomedical sciences with experience in the application of basic statistical analysis techniques to a variety of biological problems.
The course will combine lectures on statistics and practical exercises, during which the participants will learn how to work with the widely used "R" language and environment for statistical computing and graphics.
Topics covered during the course include: reminders about numerical and graphical summaries, and hypothesis testing; multiple testing, linear models, correlation and regression, dimensionality reduction such as principal component analysis, heatmaps and the basis of clustering algorithms. Participants will also have the opportunity to ask questions about the analysis of their own data.
Audience
This typical profile is a biologist needing to perform statistical analyses using R.
Learning outcomes
At the end of the course, the participants are expected to:
- choose the right method to summarize a dataset, graphically and numerically
- perform basic hypothesis tests on a datatest
- assess whether different variables are linked, using correlation and regression analysis
- use the R statistical package to run statistical analyses and interpret their outcome
- use dimensionality reduction to overcome problems of big data
- perform clustering on datasets
- visualise complex data using heatmaps.
Prerequisites
Technical: Knowledge / competencies:- No prior statistical knowledge is required in order to attend the course
- Participants do not need any experience in R before the course
Application
Registration fees for academics are 240 CHF and 1200 CHF for for-profit companies.
Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.
Deadline for free-of-charge cancellation is set to *26/01/2021*. Cancellation after this date will not be reimbursed. Please note that participation in SIB courses is subject to our [general conditions](https://www.sib.swiss/training/terms-and-conditions).Venue & Time
This course will be streamed.
The course will start at 9:00 and end around 17:00 every day. Precise information will be provided to the participants on due time.
Additional information
Coordination: Valeria Di Cola.We will recommend 1 ECTS credits for this course (given a passed exam at the end of the course).
You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
Please note that participation in SIB courses is subject to our general conditions.
SIB abides by the ELIXIR Code of Conduct. Participants of SIB courses are also required to abide by the same code.
For more information, please contact training@sib.swiss.