Question 1 Exploratory Data Analysis

Question 1

Which of the following is a principle of analytic graphics?

Don’t plot more than two variables at at time
Show multivariate data
Show box plots (univariate summaries)
Make judicious use of color in your scatterplots
Only do what your tools allow you to do

According to six principles stated during the video Principles of Analytic Graphics:

Principle 1: Show comparisons

Principle 2: Show causality, mechanism, explanation

Principle 3: Show multivariate data

Principle 4: Integrate multiple modes of evidence

Principle 5: Describe and document the evidence

Principle 6: Content is king

Question 2

What is the role of exploratory graphs in data analysis?

Axes, legends, and other details are clean and exactly detailed.
They are typically made very quickly.
They are made for formal presentations.
Only a few are constructed.

According to the Summary of Exploratory Graphs document.

Exploratory plots are “quick and dirty”

Let you summarize the data (usually graphically) and highlight any broad features

Explore basic questions and hypotheses (and perhaps rule them out)

Suggest modeling strategies for the “next step”

Question 3

Which of the following is true about the base plotting system?

Plots are created and annotated with separate functions
Margins and spacings are adjusted automatically depending on the type of plot and the data
Plots are typically created with a single function call
The system is most useful for conditioning plots

According to the Summary of The Base Plotting System in R document.

Plots in the base plotting system are created by calling successive R functions to “build up” a plot

Plotting occurs in two stages:

Creation of a plot

Annotation of a plot (adding lines, points, text, legends)

The base plotting system is very flexible and offers a high degree of control over plotting

Question 4

Which of the following is an example of a valid graphics device in R?

Based on slides 6 and 7 from Graphics Devices in R document.

Vector formats: pdf, svg, win.metafile, and postscript, and;

Bitmap formats: png, jpeg, tiff, and bmp.

Question 5

Which of the following is an example of a vector graphics device in R?

Based on slide 6 from Graphics Devices in R document.

Vector formats: pdf, svg, win.metafile, and postscript, and;

Question 6

Bitmapped file formats can be most useful for

Scatterplots with many many points
Plots that are not scaled to a specific resolution
Plots that require animation or interactivity
Plots that may need to be resized

According to the Summary of Graphics Devices in R in R document.

Plots must be created on a graphics device

The default graphics device is almost always the screen device, which is most useful for exploratory analysis

File devices are useful for creating plots that can be included in other documents or sent to other people

For file devices, there are vector and bitmap formats

Vector formats are good for line drawings and plots with solid colors using a modest number of points

Bitmap formats are good for plots with a large number of points, natural scenes or webbased plots

Question 7

Which of the following functions is typically used to add elements to a plot in the base graphics system?

text()
plot()
boxplot()
hist()

Based on slide 13 from The Base Plotting System in R document.

plot: make a scatterplot, or other type of plot depending on the class of the object being plotted

lines: add lines to a plot, given a vector x values and a corresponding vector of y values (or a 2-

column matrix); this function just connects the dots

points: add points to a plot

text: add text labels to a plot using specified x, y coordinates

title: add annotations to x, y axis labels, title, subtitle, outer margin

mtext: add arbitrary text to the margins (inner or outer) of the plot

axis: adding axis ticks/labels

Question 8

Which function opens the screen graphics device for the Mac?

quartz()
png()
bitmap()
pdf()

Based on slide 2 from Graphics Devices in R document.

A graphics device is something where you can make a plot appear

A window on your computer (screen device)

A PDF file (file device)

A PNG or JPEG file (file device)

A scalable vector graphics (SVG) file (file device)

When you make a plot in R, it has to be “sent” to a specific graphics device

The most common place for a plot to be “sent” is the screen device

On a Mac the screen device is launched with the quartz()

On Windows the screen device is launched with windows()

On Unix/Linux the screen device is launched with x11()

Question 9

What does the ‘pch’ option to par() control?

the orientation of the axis labels on the plot
the size of the plotting symbol in a scatterplot
the plotting symbol/character in the base graphics system
the line width in the base graphics system

Based on slide 9 from The Base Plotting System in R document.

pch: the plotting symbol (default is open circle)

lty: the line type (default is solid line), can be dashed, dotted, etc.

lwd: the line width, specified as an integer multiple

col: the plotting color, specified as a number, string, or hex code; the colors() function gives

you a vector of colors by name

xlab: character string for the x-axis label

ylab: character string for the y-axis label

Question 10

If I want to save a plot to a PDF file, which of the following is a correct way of doing that?

Construct the plot on the PNG device with png(), then copy it to a PDF with dev.copy2pdf().
Construct the plot on the screen device and then copy it to a PDF file with dev.copy2pdf()
Open the screen device with quartz(), construct the plot, and then close the device with dev.off().
Open the PostScript device with postscript(), construct the plot, then close the device with dev.off().

Based on slide 9 from Graphics Devices in R document.

Copying a plot to another device can be useful because some plots require a lot of code and it can be a pain to type all that in again for a different device.

dev.copy: copy a plot from one device to another

dev.copy2pdf: specifically copy a plot to a PDF file

`Question 1` Exploratory Data Analysis

👨🏻‍💻 Anderson H Uyekita