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Course description

The BYOD course on publication-quality figures is a course that teaches the ggplot2 package in R. Ggplot2 is an implementation of the Grammer of Graphics. It allows you to make nearly any figure you can think of. During a BYOD course, we encourage you to apply lessons learned directly to your own data. Alternatively, you can borrow or download data that is relevant to you. You will also practice and explore which visualisations work best for your dataset. While an ordinary visualisation will represent your data honestly and some pattern of interest will be visible, a strong visualisation makes those patterns evident and intuitive.

Please note that your data should be in a shape that can easily be imported into R.

This course is aimed at PhD candidates that have experience in basic R programming and who want to improve the quality of their figures. You don’t need experience with ggplot2, but we also welcome PhD candidates familiar with ggplot2 who want to improve their understanding and usage thereof.

Requirements

When you register for this BYOD course, we expect you to have experience in basic R. See if the following statements apply to test if this is the case for you:

• You are comfortable loading and exploring data in R as well as simple data manipulations.
• You know about data types (numeric, character, logical, factor) and various object types (vector, matrix, data frame).
• You can subset and reorder your data and make simple plots with base R functions like plot()
• You have written an R script that logically processes data to some end result, such as a figure or summarising table.
• You can apply most or all skills on the Base R cheatsheet without help:

Experience in the following topics will help you but is not required:

• Some experience with ggplot2.
• Rmarkdown and Rstudio.
• You use apply, for-loops and self-written functions in your R scripts.

If you do not meet this level yet, be welcome in the Intro to R course we offer via the PhD Course Centre.

During this course, you will work on your own laptop with R and Rstudio installed!

Learning objectives

After successfully completing this course, you:

• Can flexibility reformat your data for visualisation.
• You understand the layers of the Grammar of Graphics implemented in R and you can use it to your advantage.
• You can choose and experiment with visualisation types that suit a particular dataset or pattern found in a dataset, in order to make patterns visually evident and intuitive.
• You can tweak a visualisation with proper usage of colour and scales.
• You can tweak non-data elements like labels and axes to fit publisher requirements.
• You can export and optimise figures in a publication-ready format.

In this course, we will make many figures of the dataset(s) you bring. We focus on choosing, optimising and polishing these visualisations for publication. We do not go in-depth on the proper statistics for each particular experiment or cleaning (very) dirty data.

Instructional method

During this course, you will work on your own laptop. A week before the course starts, you will receive an email with instructions on how to install the required software. Classes during the week start with in-class lectures, hands-on exercises and Q&A sessions. As the week progresses, fewer exercises are provided and you will work predominantly on your own data. At the end of the course, you will shortly present and discuss one of the figures you have made during the course to share your progress.

Trainer

You will be trained by one of the professionals of Utrecht ľ¹Ï¸£ÀûÓ°ÊÓ.

Group size            

Groups are small to ensure sufficient supervision time for all data-set-specific questions. We allow 20 participants in the course. Depending on demand, the course may be organised more frequently.

Number of credits                                 

1.5 EC

Course schedule

Study load

Next to the in-class lectures, hands-on exercises and Q&A sessions, you will spend the vast majority of your time on data analysis during the week of the course. In this way you gain as much as possible from the in-class sessions.

Course certificate                                

You will receive a course certificate after actively participating in all course sessions, including presenting and discussing one of the figures you have made.

Cancellation and No-show policy

This course is free for GSLS PhD candidates. However: free of charge does not mean free of responsibility. Once you have signed up for a course, we expect you to attend. For every late cancellation or no-show we have had to disappoint others who would have liked to attend. This is our policy:

• You may cancel free of charge up to 4 weeks before the start of the course. After this date you can only cancel if you have a GSLS PhD candidate to replace you in the course. Send the name and contact information of your replacement to pcc@uu.nl, at least 2 working days before the start of the course;
• We expect that you actively attend the full course, but at least 80%. It is mandatory to attend the first session. If you are absent the first session you cannot follow the remaining of the course;
• Not meeting the above requirements means you will be charged a no-show fee (€ 75). We will send the invoice after the course has ended. We are unable to make any exceptions, unless you have a valid reason (i.e., illness or death in the family 1^st/2^nd degree or partner). Your supervisor has to send an e-mail to pcc@uu.nl indicating the reason.

Unfortunately we don’t offer this course for participants not part of the GSLS. Our courses tend to be fully booked by GSLS PhD candidates.