Box Plot

http://processtrends.com/pg_chart_box_plot.htm

This is a standard box plot showing a comparison between four different groups and sales ranging from 0-6,000.  The legend at the side shows the viewer exactly what the symbols mean and what they are looking at. A box plot is basically a picture or graphic that centralizes the data and shows the range of percentiles like that of this example.

Parallel Coordinate Graph

 

http://gis.cancer.gov/nci/geovisualization.html

This is a parallel coordinate graph used to communicate cancer statistics.  A parallel coordinate graph shows multiple variables on a geographic projection where each individual line represents a different variable.  This type of map would be quite useful because common trends between variables would be easily visible. 

Lorenz Curve

http://www.bized.co.uk/reference/diagrams/Lorenz-Curve/
This image is a Lorenz curve and is used for economic analysis of distribution of wealth within countries.  The Y-axis describes cumulative share of income and the X-axis cumulative share of population.  The straight line represents the line of perfect equality and the curved line is lorenz curve.  Following along the lorenz curve will tell the viewer how much of the population holds how much of the cumulative income of the country.  The closer the curved line is to the line of perfect equality, the more equally distributed the wealth is in that country.  In a perfect world the bottom 40% will hold 40% of the total wealth, the top 20% will hold 20% of the wealth and so on.

Univariate Choropleth

 

I created this map via ArcMap

This is a univariate choropleth map showing female literacy rates by province in Afghanistan during the years 2007 and 2008.  The lighter colors show a lower literacy rate by percentage and the darker colors showing a higher literacy rate.  A univariate map displays one variable on a geographic projection such as the one above.  I created this map using ArcGIS and downloaded the shapefiles from geocommons.com.

Bivariate Choropleth

 

I created this map using ArcGIS

This is almost the same exact map I used below as a classed choropleth map except I introduced a second variable.  A bivariate choropleth map basically displays two variables on one map.  Again, the color densities show GDP per capita by state in 2007 with California, Texas, and New York having the highest.  The second variable I added is top national colleges in the states which is shown by the blue triangles.  I chose to display top schools in America and compare it to GDP per state because I wanted to see if there was a relationship between education and productivity.  As you can see from the map, there are many prestigious universities in the top states with highest GDP and the states in the west (Wyoming, Montana, Idaho, N and S Dakota) that are among the lowest GDP do not have any universities. I created this map using ArcGIS and downloaded the shapefiles from geocommons.com. 

Classed Choropleth

I created this map using ArcGIS

This is a map of GDP per capita by state in the years 2007.  I created this map using ArcGIS and downloaded the shapefiles from geocommons.com.  I decided to classify the data into natural breaks and created six classes.  The darker the color the higher the GDP as can be seen in California, Texas, and New York.  Data can be displayed by many different classifications and completely change the message of the map even though the same information is used.  I thought that natural breaks was the least misleading for this dataset.

Correlation Matrix

http://yin.che.wisc.edu/images.htm

A correlation matrix is symmetric in shape and shows correlation between two numerical values in a graphical form.  This is a calculated protein correlation matrix with a range from 0.1 (blue-lowest) to 1 (red-highest).  This type of matrix is efficient in displaying correlation between two different variables.