Reproducible Research in Practice: Make your scientific writing, data analysis and results transparent with Quarto and R.

Course Description

Scientific writing is more than just putting words on paper. It is about presenting your data, methods, and results in a clear, transparent, and reproducible way. In this course, you’ll learn how to streamline your research workflow by integrating statistical analysis, narrative writing, and figure generation into one coherent process.

We focus on replacing the traditional fragmented and error-prone workflow (storing data in e.g. Excel, creating figures in Excel/R/SPSS/etc, writing in Word and endlessly copy-pasting everything together) with a modern, reproducible approach using Quarto and R/RStudio.

Quarto allows you to combine the writing of your manuscript and your statistical analysis into a single dynamic document that can be rendered into HTML, PDF, or Word. The result: more efficient writing, fewer mistakes, and documents that you (and others) can update and re-run at any time. Adding or removing data no longer means starting over again.

Learning outcomes

You will learn how to:

• Integrate data analysis, results, and your manuscript text using Quarto
• Render your work into publishable formats (PDF, HTML, Word)
• Reuse or adapt content and figures without copy-paste chaos
• Manage references and citations using a bibliography file
• Create well-formatted tables and mathematical equations
• Combine multiple manuscripts into a single document, such as a PhD thesis
• Build workflows that your future self will still understand

Who is this course for?

This course is designed for researchers, PhD candidates, and teachers who:

• write scientific reports, papers, or teaching materials
• use R for data analysis (basic knowledge is required)
• want to improve the reproducibility, transparency, and reusability of their work

Requirements:

Familiarity with R and basic statistical concepts is expected. For example, participants are recommended to have completed the VLAG course “Introduction to R”, and either “Applied Statistics”, “Chemometrics”, or an equivalent course. Participants will benefit most from this course if they are already actively working on data analysis and manuscript writing in the context of their own research.

Lecturer:

Jos Hageman (Biometris)

Course dates and venue:

17 and 21 November 2025, 2 days from 9:00-17:00hrs, on Campus WUR

Study load:

The study load of this course is 0.6 ECTS credits.

Registration & Costs:

Costs includes material, tea/coffee and lunches (sandwiches).
* VLAG/EPS/PE&RC/WASS/WIAS/WIMEK PhD candidates with an approved TSP.

Cancellation policy:

• No charge until one month before the start of the course
• 25% of the course fee paid or due till 7 days before the start of the course
• No refund after 7 days before the start of the course

Information:

For more information please contact Yvonne Smolders