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Instructor-led course

Provided by: Bioinformatics

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Basic statistics and data handling


This three day course is intended to open doors to applying statistics - whether directly increasing skills and personally undertaking analyses, or by expanding knowledge towards identifying collaborators. The end goal is to drive confident engagement with data analysis and further training - increasing the quality and reliability of interpretation, and putting that interpretation and subsequent presentation into the hands of the researcher. Each day of the course will deliver a mixture of lectures, workshops and hands-on practicals – and will focus on the following specific elements.

Day 1 focuses on basic approaches and the computer skills required to do downstream analysis. Covering: Basic skills for data manipulation in R. How to prepare your data effectively. Principles of experimental design and how this influences analysis.

On day 2, participants will explore the core concepts of statistics – so that they can begin to see how they can be applied to their own work, and to also help with better critical evaluation of the work of others. Covering: Basic statistics concepts and practice: power, variability, false discovery, t-test, effect size, simulations to understand what a p-value means.

On day 3 we will continue to explore core concepts of statistics, focusing on linear regression and multiple testing correction.

Course materials are available here.

This event is supported by a BBSRC Strategic Training Awards for Research Skills (STARS) grant.

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

Target audience
  • The course is aimed primarily at mid-career scientists – especially those whose formal education likely included statistics, but who have not perhaps put this into practice since.
  • Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
  • Further details regarding eligibility criteria are available here
Topics covered

Bioinformatics, Data handling, Data visualisation, Statistical calculation


During this course you will learn about:

  • Planning your experiment and why good experimental design is critical
  • How to use spreadsheet programs (such as Excel) more effectively, and the limitations of such programs
  • Writing and executing basic data analysis workflows in R
  • Formulating and interpreting the result of a statistical test
  • Choosing the appropriate graphics to understand and present your data

After this course you should be able to:

  • Identify sources of variation and confounding factors in your experimental design
  • Assess the distribution of your data and choose the appropriate statistical test; recognising any limitations that may exist
  • Create a reproducible piece of R code to import, visualise and perform a statistical test on biological data
  • Know how to develop your data analysis skills after the course

Presentations, demonstrations and practicals


Day 1 Topics Speaker(s)
9:30 – 10:30 Lecture: Experimental design Aaron Lun
10:30 – 12:30 Lecture/practical: Data organization and introduction to R Hugo Tavares, Sandra Cortijo
12:30 - 13:30 Lunch
13:30 – 17:30 Lecture/practical: Data manipulation in R Hugo Tavares, Sandra Cortijo
Day 2
9:30 – 10:30 Lecture: Introduction to Statistics + Descriptive analysis

Catalina Vallejos, Aaron Lun
10:30 – 11:00 Lecture: Descriptive analyses with R markdown

Catalina Vallejos, Aaron Lun
11:00 – 12:30 Lecture: Statistical inference (up to the definition of a p-value)

Catalina Vallejos, Aaron Lun
12:30 - 13:30 Lunch
13:30 – 17:30 Lecture/practical: Statistics in R: tests to compare 2 populations

Catalina Vallejos, Aaron Lun
Day 3
9:30 – 12:30 Lecture/practical: Statistics in R: linear regression

Catalina Vallejos, Aaron Lun
12:30 - 13:30 Lunch
13:30 – 15:30 Lecture/practical: Statistics in R: linear regression Cont'd

Catalina Vallejos, Aaron Lun
15:30 – 16:30 Lecture/practical: Multiple testing correction

Catalina Vallejos, Aaron Lun
Registration fees
  • Free for University of Cambridge students
  • £ 50/day for all University of Cambridge staff, including postdocs, 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

3 days


Three times a year

Related courses
Core skills

Events available