Welcome

Published

3 March, 2026

Reproducible reports with Quarto

Overview

This on-line workshop introduces you to Quarto, a scientific and technical publishing system designed to facilitate reproducible working practices by allowing you to integrate code, results, and narrative text in a single document. Quarto supports multiple programming languages, including R, Python, Julia, and Observable JavaScript.

The workshop will be taught using R and RStudio, but the concepts are applicable to other programming languages supported by Quarto. Some familiarity with the layout of RStudio and beginner level knowledge of R is assumed.

By the end of this workshop, participants will be able to transform raw data into a professional, polished report (HTML, Word, or PDF) where the text and analysis remain in sync. We will use the Gapminder data on global development to demonstrate how to produce a reproducible country profile report that analyses the relationship between wealth (GDP per capita) and health (Life Expectancy) over the last 50 years.

Audience

This workshop is intended for researchers and research support staff in academia or industry or others that regularly produce reports with data analysis.

How to sign-up

The on-line workshop is on 22 April 2026 1400 - 1600 GMT

Register for the workshop

Learning objectives

Participants will learn how to:

  • Construct a structured Quarto (.qmd) document using YAML headers to define metadata (title, author, table of contents).
  • Format narrative text using Markdown syntax to create headers, lists, and emphasis without relying on word processor GUIs.
  • Integrate R code chunks into prose to produce tables and visualizations directly within the document.
  • Implement “Inline Code” to insert dynamic statistics (e.g., specific means or p-values) directly into sentences, ensuring numbers update automatically if the data changes.
  • Control report output using “Chunk Options” to hide raw code from the final reader while keeping the results visible.
  • Render a single source document into multiple output formats (HTML for web, MS Word for collaboration, or PDF for publication).

Instructor

Emma Rand is a Professor in the Department of Biology at the University of York where she specializes in teaching data science and reproducibility, particularly to those who do not see themselves as programmers. She leads a UKRI funded projects called Cloud-SPAN and the UKRI Digital Research Skills Catalyst.