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Learn how to create clear, professional and publication-quality graphics using R.
Effective data visualisation is an essential skill for researchers, consultants, analysts and anyone who needs to communicate evidence clearly. This practical course focuses on transforming data into informative and visually appealing figures using the powerful ggplot2 package, alongside a range of complementary visualisation tools within R.
Through live online teaching, guided exercises and worked examples, participants will learn how to design figures that communicate key messages, avoid common pitfalls, and meet the standards expected in scientific publications, consultancy reports and professional presentations.
Each session combines tutor-led demonstrations with hands-on exercises, allowing participants to build a portfolio of visualisation techniques that can be applied immediately to their own work.
As part of the course, participants receive:
Two live online teaching sessions
A comprehensive course handbook and reference guide
All R code used during the course
Example datasets and worked examples
Additional self-paced learning materials and exercises
Opportunities to apply techniques to your own datasets
Topics covered include:
Principles of effective data visualisation
Introduction to the Grammar of Graphics (ggplot2)
Creating charts and figures using ggplot2
Customising themes, colours and layouts
Producing publication-quality graphs
Visualising distributions, trends and relationships
Multi-panel figures and faceting
Mapping and spatial visualisation basics
Visualising model outputs and uncertainty
Exporting high-quality graphics for reports, publications and presentations
Common mistakes in data visualisation and how to avoid them
By the end of the course, you will be able to produce clear, professional and visually engaging graphics in R, select appropriate visualisation techniques for different types of data, and communicate analytical results more effectively to a wide range of audiences.
Prerequisites: Participants should have a basic familiarity with R and RStudio. Completion of our Introduction to Data Analysis with R course, or equivalent experience, is recommended.
Fee: £110 + VAT (£132)
Learn how to create clear, professional and publication-quality graphics using R.
Effective data visualisation is an essential skill for researchers, consultants, analysts and anyone who needs to communicate evidence clearly. This practical course focuses on transforming data into informative and visually appealing figures using the powerful ggplot2 package, alongside a range of complementary visualisation tools within R.
Through live online teaching, guided exercises and worked examples, participants will learn how to design figures that communicate key messages, avoid common pitfalls, and meet the standards expected in scientific publications, consultancy reports and professional presentations.
Each session combines tutor-led demonstrations with hands-on exercises, allowing participants to build a portfolio of visualisation techniques that can be applied immediately to their own work.
As part of the course, participants receive:
Two live online teaching sessions
A comprehensive course handbook and reference guide
All R code used during the course
Example datasets and worked examples
Additional self-paced learning materials and exercises
Opportunities to apply techniques to your own datasets
Topics covered include:
Principles of effective data visualisation
Introduction to the Grammar of Graphics (ggplot2)
Creating charts and figures using ggplot2
Customising themes, colours and layouts
Producing publication-quality graphs
Visualising distributions, trends and relationships
Multi-panel figures and faceting
Mapping and spatial visualisation basics
Visualising model outputs and uncertainty
Exporting high-quality graphics for reports, publications and presentations
Common mistakes in data visualisation and how to avoid them
By the end of the course, you will be able to produce clear, professional and visually engaging graphics in R, select appropriate visualisation techniques for different types of data, and communicate analytical results more effectively to a wide range of audiences.
Prerequisites: Participants should have a basic familiarity with R and RStudio. Completion of our Introduction to Data Analysis with R course, or equivalent experience, is recommended.
Fee: £110 + VAT (£132)