The document provides an introduction to the Stat405 statistical computing and graphics course taught by Hadley Wickham. It includes the syllabus, an introduction to using Linux and R, and examples of basic graphics in R like scatterplots and faceting. Students are encouraged to experiment with different aesthetics and geoms in their plots and to keep code organized in a text editor.

1. Stat405
Statistical computing & graphics
Hadley Wickham

2. 1. Introductions
2. Syllabus
3. Introduction to linux
4. Introduction to R
5. Basic graphics

3. HE LL O
my name is
Hadley

4. had.co.nz/stat405
(if you can’t remember just google stat405)
hadley@rice.edu

5. About me
From New Zealand
Divisional advisor for McMurtry
Major advisor for statistics

6. Syllabus

7. Introduction to linux

8. Essential tools
The terminal to run R. gedit to edit your R
code.
To load the terminal, right-click on the
desktop.
To load R, type R in the terminal. To load
gedit, type gedit & in the terminal (the &
tells it to run separately). To open a file in
gedit, type gedit filename &

9. Setup
Work through the instructions at http://
had.co.nz/stat405/linux.html.
I’ll circulate and make sure everyone gets
set up right.

10. Terminal essentials
Mouse select = Copy
Middle button = Paste
Ctrl + A = home
Ctrl + D = end
Alt + tab = change applications
Press tab to complete file names

11. Introduction to R

12. Learning a new
language is hard!

13. Scatterplot basics
install.packages("ggplot2")
library(ggplot2)
?mpg
head(mpg)
str(mpg)
summary(mpg)
qplot(displ, hwy, data = mpg)

14. Scatterplot basics
install.packages("ggplot2")
library(ggplot2)
?mpg
head(mpg)
str(mpg)
Always explicitly
summary(mpg) specify the data
qplot(displ, hwy, data = mpg)

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qplot(displ, hwy, data = mpg)
displ

16. Additional variables
Can display additional variables with
aesthetics (like shape, colour, size) or
facetting (small multiples displaying
different subsets)

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● ● class
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● 2seater
30 ● ● ● ● compact
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● midsize
hwy
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● ● ●● ● ● ● ● ● minivan
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● subcompact
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qplot(displ, hwy, colour = class, data = mpg)
displ

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● midsize
hwy
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qplot(displ, hwy, colour = class, data = mpg)
displ

19. Your turn
Experiment with colour, size, and shape
aesthetics.
What’s the difference between discrete or
continuous variables?
What happens when you combine
multiple aesthetics?

20. Discrete Continuous
Rainbow of Gradient from
Colour
colours red to blue
Linear mapping
Discrete size
Size between radius
steps
and value
Different shape
Shape Doesn’t work
for each

21. Faceting
Small multiples displaying different
subsets of the data.
Useful for exploring conditional
relationships. Useful for large data.

22. Your turn
qplot(displ, hwy, data = mpg) +
facet_grid(. ~ cyl)
qplot(displ, hwy, data = mpg) +
facet_grid(drv ~ .)
qplot(displ, hwy, data = mpg) +
facet_grid(drv ~ cyl)
qplot(displ, hwy, data = mpg) +
facet_wrap(~ class)

23. Summary
facet_grid(): 2d grid, rows ~ cols, . for
no split
facet_wrap(): 1d ribbon wrapped into 2d

24. Aside: workflow
Keep a copy of the slides open so that
you can copy and paste the code.
For complicated commands, write them
in gedit and then copy and paste.

25. What’s the ● ●
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qplot(cty, hwy, data = mpg)
cty

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qplot(cty, hwy, data = mpg, geom = "jitter")
cty

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2seater compact midsize minivan pickup subcompact suv
qplot(class, hwy, data = mpg)
class

29. How could ● ●
we improve
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this plot? ●
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Brainstorm ●
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for 1 minute.
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2seater compact midsize minivan pickup subcompact suv
qplot(class, hwy, data = mpg)
class

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pickup suv minivan 2seater midsize subcompact compact
reorder(class, hwy)

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technique!
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pickup suv minivan 2seater midsize subcompact compact
qplot(reorder(class, hwy), hwy, data = mpg)
reorder(class, hwy)

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pickup suv minivan 2seater midsize subcompact compact
qplot(reorder(class, hwy),reorder(class, hwy) = mpg, geom = "jitter")
hwy, data

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reorder(class, =

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qplot(reorder(class,minivan
pickup suv
hwy), 2seater data = subcompact
hwy, midsize mpg, compact
geom = c("jitter", "boxplot"))
reorder(class, hwy)

35. Your turn
Read the help for reorder. Redraw the
previously plots with class ordered by
median hwy.
How would you put the jittered points on
top of the boxplots?

36. Aside: coding strategy
At the end of each interactive session, you
want a summary of everything you did. Two
options:
1. Save everything you did with savehistory()
then remove the unimportant bits.
2. Build up the important bits as you go.
(this is how I work)