Organizer: University of Cambridge

Host institution: University of Cambridge Bioinformatics Training

Start: Monday, 13 May 2019 @ 08:30

End: Tuesday, 14 May 2019 @ 16:30

Venue: Craik-Marshall Building

City: Cambridge

Country: United Kingdom

Postcode: CB2 3AR

Scientific topic: Biology, Bioinformatics

Target audience:
  • Graduate students
  • Postdocs and Staff members from the University of Cambridge
  • Institutions and other external Institutions or individuals
Description:

R is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research.

In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided.

The course website providing links to the course materials is here.

Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of Related courses. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on Data Analysis and Visualisation in R course.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.''

Event type:
  • Workshops and courses
An Introduction to Solving Biological Problems with R https://tess.elixir-europe.org/events/an-introduction-to-solving-biological-problems-with-r-db83e376-b356-4e0f-bacf-f08608c3345f [R](https://www.r-project.org/) is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research. In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided. The course website providing links to the course materials is [here](http://cambiotraining.github.io/r-intro/). Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of Related courses. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on [Data Analysis and Visualisation in R](http://training.csx.cam.ac.uk/bioinformatics/course/bioinfo-intR) course. This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1). The training room is located on the first floor and there is currently no wheelchair or level access available to this level. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book or register your interest by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=2823227&course-title=An%20Introduction%20to%20Solving%20Biological%20Problems%20with%20R).'' 2019-05-13 08:30:00 UTC 2019-05-14 16:30:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Biology Bioinformatics University of Cambridge Bioinformatics Training [] Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] []