Basic statistics and data handling

Beginners

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 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 by linking here.

• 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
• Please be aware that these courses are only free for 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

Number of sessions: 3

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

• 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

Three times a year

• Introduction to Scientific Figure Design (ONLINE LIVE TRAINING)
• Statistical Analysis using R
• An Introduction to Solving Biological Problems with R
• CRUK: Data Carpentry in R