Detaild Lecture Outline and Additional Resources

Resources associated with each section of the lecture.

Detailed outline and resources

Here is the outline of the lecture, along with links to additional resources on each topic.

Introduction

Usefulness and importance

• Explore and explain
  • Why looking at data?
  • Existing tools for exploratory data analysis in R
• Deceptive visualizations
  • Defense against dishonest charts

Key data viz principles

• Perception and color
  • More on Gestalt principles (plus a research article)
  • How to find and create good color palettes on
• Data-to-ink ratio
  • A critique of the data-to-ink ratio
• Aesthetics
  • Reasons to make beautiful graphs on
  • Credibility and typography
  • In defense of simple charts

Building a graph

• Graph galeries
  • Data Viz Project
  • Flowing Data - Chart type
  • Dataviz Inspiration
  • R graph gallery
• What questions to ask when creating charts
• Decision trees for a graph type
  • Financial Times tree
  • Data viz catalogue
  • Datawrapper guide
  • Data to viz graph
• Concrete recommendations
  • For color
  • For text
• Specific do’s and don’ts
  • Statistics oriented
  • A collection of dataviz caveats
  • Sometimes it’s ok to break the rules

Data viz for research in economics

• When do we use graphs in econ?
• Specificities of viz in econ
  • Avoid overplotting
  • Visualize regression output
  • Visualize regression output with distributions

Main take-away messages

Slides

Open slides in html

Open slides in PDF