Week 2: Data Visualisation with R, Statistical Communication and Workflow

Practical Skills: Data Visualisation with R, Literate Programming

Slides

Data Visualisation with R

• Grammar of graphics
• Position adjustments and coordinate systems
• Multiple layers with ggplot2

Statistical Communication and Workflow

• Importing and exporting data
• What is Quarto?
• Meta data with YAML
• Text with Markdown
• Dynamic documents with data analysis code
• Cross references
• Towards better reproducible practice

Performance Outcomes

You should feel confident to perform the following outcomes:

R programming

• Import data in various files like csv, tsv and excel files into R

Data visualisation

• Create basic plots using ggplot2
• Understand the concept of the grammar of graphics
• Facilitate data exploration by adding layers (e.g., facets, smoothers, annotations) to ggplot2 visualizations

Literate programming

• Generate HTML, PDF, or Word documents using Markdown syntax
• Understand the anatomy of Quarto documents
• Develop dynamic documents containing code using Quarto
• Implement various code chunk options to customize chunk behaviour
• Recognize the significance of reproducibility and grasp the concept of literate programming
• Apply reproducible practices
• Establish an organized folder structure for data projects

Resources

If you don’t feel yet confident after going through the teaching materials or would like further resources, then you are also encouraged to go through the following materials.

• Statistical Inference via Data Science: A ModernDive into R and the Tidyverse (2nd Edition)
  • Chapter 2: Data Visualization
• R for Data Science (2nd Edition)
  • Chapter 1: Data visualization
  • Chapter 7: Data import
  • Chapter 9: Layers
  • Chapter 10: Exploratory data analysis
  • Chapter 20: Spreadsheets
  • Chapter 28: Quarto
  • Chapter 29: Quarto formats
• Data Visualsiation with ggplot2 Cheatsheet Cheatsheet
• Publish and Share with Quarto Cheatsheet

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