# Take a look at the variables in this data frame…

What kind of variable is GDP and population?

# What about Total?

# To examine the relationship between these three variables,

# we could consider making a scatter plot of GDP against pop

# and use plotting symbols that are proportional in size to

# the number of medals.

# To begin, make a plot of GDP against population.

# Which of the three principles of good graphics does this

# plot violate and why?

#Q7. Let’s examine GDP per person (create this new varialbe your self)

# and population. Use a log scale for both axes. Use the symbols()

# function rather than plot(), and create circles for the plotting

# symbols where the area of the circle is proportional to the

# total number of medals.

# Q8. It appears that the countries with no medals are circles too.

# Remake the plot, this time using only the countries that won

# medals. Then add the non-medal countries to the plot using the “.” plotting

# character.

# Q9. Make the plot information rich by adding axis labels,

# title, and label at least 5 of the more interesting points

# with the country name. Use text() to do this.

# PRINT A COPY OF THIS PLOT TO TURN IN.

######################################

# PLOT 3.

# Plotting points on maps can help us see geographic relationships

#

#Q10. Install the maps library and load it into your R session.

# Make a map of thw world where the countries are filled with a light grey color.

#Q11. Use the symbols() function to add circles to the map where

# the circles are proportional in area to the number of medals

# won by the country. You may find the add parameter useful.

# (Be sure to NOT plot circles for countries with 0 medals).

#Q12. Remake the plot and fill in the circles with a partially

# transparent gold color. To create this color:

# install the RColorBrewer library and load it into R;

# call display.brewer.all() to examine the palettes;

# choose a palette and ask for the names of a few colors

# using brewer.pal();

# pick one of the colors and create a new one that is transparent

# by adding two more digits to the end of the name, e.g.,

# if you want to use “#FEB24C” then make it transparent with

# e.g. myColor = “#FEB24CAA” or “#FEB24C88”

# What about Total?

# To examine the relationship between these three variables,

# we could consider making a scatter plot of GDP against pop

# and use plotting symbols that are proportional in size to

# the number of medals.

# To begin, make a plot of GDP against population.

# Which of the three principles of good graphics does this

# plot violate and why?

#Q7. Let’s examine GDP per person (create this new varialbe your self)

# and population. Use a log scale for both axes. Use the symbols()

# function rather than plot(), and create circles for the plotting

# symbols where the area of the circle is proportional to the

# total number of medals.

# Q8. It appears that the countries with no medals are circles too.

# Remake the plot, this time using only the countries that won

# medals. Then add the non-medal countries to the plot using the “.” plotting

# character.

# Q9. Make the plot information rich by adding axis labels,

# title, and label at least 5 of the more interesting points

# with the country name. Use text() to do this.

# PRINT A COPY OF THIS PLOT TO TURN IN.

######################################

# PLOT 3.

# Plotting points on maps can help us see geographic relationships

#

#Q10. Install the maps library and load it into your R session.

# Make a map of thw world where the countries are filled with a light grey color.

#Q11. Use the symbols() function to add circles to the map where

# the circles are proportional in area to the number of medals

# won by the country. You may find the add parameter useful.

# (Be sure to NOT plot circles for countries with 0 medals).

#Q12. Remake the plot and fill in the circles with a partially

# transparent gold color. To create this color:

# install the RColorBrewer library and load it into R;

# call display.brewer.all() to examine the palettes;

# choose a palette and ask for the names of a few colors

# using brewer.pal();

# pick one of the colors and create a new one that is transparent

# by adding two more digits to the end of the name, e.g.,

# if you want to use “#FEB24C” then make it transparent with

# e.g. myColor = “#FEB24CAA” or “#FEB24C88”

Don't use plagiarized sources. Get Your Custom Essay on

Take a look at the variables in this data frame…

Just from $13/Page

Attachments: