Looking at Data (a)

Soc 690S: Week 01

Kieran Healy

Duke University

January 15, 2025

Data Visualization
with R and ggplot2

Get up and Running

Course Materials

Course Website

Course Notes

Canvas Website

  • Where you’ll submit assignments

Try rendering your notes

  • Don’t worry if it’s not clear what’s happening at this point.

Now write the following code

Write this out inside the “code chunk” in your notes.

p <- ggplot(data = gapminder, 
            mapping = aes(x = gdpPercap, 
                          y = lifeExp))  


p + geom_point()

… And Render your document again.

Now write the following code

Write this out inside the “code chunk” in your notes.

p <- ggplot(data = gapminder, 
            mapping = aes(x = gdpPercap, 
                          y = lifeExp))  


p + geom_point()

… And Render your document again.

You should
look at
your data

Seeing things

Anscombe’s Quartet

Desmond, Papachristos & Kirk (2016)

Zoorob (2020)

Zoorob (2020)

Cairo; Matejka & Fitzmaurice

Pew Research

  • A. In recent years, the rate of cavities has increased in many countries
  • B. In some countries, people brush their teeth more frequently than in other countries
  • C. The more sugar people eat, the more likely they are to get cavities
  • D. In recent years, the consumption of sugar has increased in many countries

Pew Research

  • A. In recent years, the rate of cavities has increased in many countries
  • B. In some countries, people brush their teeth more frequently than in other countries
  • C. The more sugar people eat, the more likely they are to get cavities
  • D. In recent years, the consumption of sugar has increased in many countries

Pew Research

  • A. In recent years, the rate of cavities has increased in many countries
  • B. In some countries, people brush their teeth more frequently than in other countries
  • C. The more sugar people eat, the more likely they are to get cavities
  • D. In recent years, the consumption of sugar has increased in many countries

Not Seeing Things

Bad Taste

Bad Data

Bad Perception

Bad Taste: Simplify, Simplify?

Tufte’s “Data to Ink Ratio”

Nigel Holmes

Darkhorse Analytics

Darkhorse Analytics

Bad Data: Junk-Free Junk Charts

New York Times

Erik Voeten

Bad Perception: Seeing and Not Seeing

Edges & Contrasts

Hermann Grid Effect

Fraser Columns

Fraser Diamonds

Mach Bands

Mach Bands

Edward Adelson

Edward Adelson

Edward Adelson

Luminance and Color

Troxler effect

Lilac Chaser

Colin Ware

Colin Ware

National Weather Service

Achim Zeileis

Achim Zeileis

Achim Zeileis