Statistics bootcamp using R (Online)

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors available to help you work through the course material on a personal copy of the course environment. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout.

This bootcamp provides an in depth look at statistical analyses using R.

Day 1 aims to introduce R as a tool for statistics and graphics, with the main aim being to become comfortable with the R environment. As well as introducing core R language concepts, this course also provides the basics of using the Tidyverse for data manipulation, and ggplot for plotting. It will focus on entering and manipulating data in R and producing simple graphs.

PLEASE NOTE: If you are already comfortable working in R and using the tidyverse package, you might find that you can skip Friday’s training session. Please review the pre-requisites section below for further information.

Day 2-6 (half days) will focus on the statistical possibilities of R, covering from experimental design to analysis of quantitative and qualitative data. Ample time will be given to participants to practise different type of analysis and interact with the trainers to discuss their statistical problems.

This event is organized in collaboration with the Babraham Institutes's Bioinformatics Group and it is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

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.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• Please be aware that these courses are only free for registered University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here.
• Further details regarding eligibility criteria are available here

If you are already comfortable working in R and using the tidyverse package, you might find that you can skip Friday’s training session.

Day 1 intends to provide you with all the R prerequisites you will need to make the most of the statistics section of the course so please only skip it if you are confident in your abilities.

If you would like to test whether you have the necessary R knowledge to skip the first day please make sure you can complete the following exercise with the data linked.

Exercise : http://www.bioinformatics.babraham.ac.uk/training/Introduction_to_R_tidyverse/Post%20Course%20Recap%20Exercise.pdf

Data : http://www.bioinformatics.babraham.ac.uk/training/Introduction_to_R_tidyverse/R_tidyverse_intro_data.zip

If you decide not to attend the first day please let us know by replying to your booking confirmation email.

Number of sessions: 6

Bioinformatics, Data handling, Statistical calculation

After this course you should be able to:

• Discuss basic principles of experimental design and power analysis
• Know how to explore your data prior to the analyses
• Discuss basic statistical principles
• Choose the appropriate statistics approach for your data
• Use R to apply classical statistical techniques on quantitative and qualitative data

During this course you will learn about:

Day 1- Full day

• The R and R Studio environments
• Variables, Functions and R Data Structures
• Using Tydiverse, a collection of R packages designed for data science
• Importing data files, entering and manipulating data
• Creating graphs (scatterplots, line graphs, line graphs, histograms and density plots)

Day 2-6 - Half days

• Experimental Design
• Sample size estimation: power analysis
• Descriptive statistics and data exploration
• Analysis of quantitative data
• Linear modelling
• Analysis of qualitative data

Presentations, demonstrations, and practicals

• Free for registered University of Cambridge students
• £ 50/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 100/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

1 full day, 5 half days