Unstandardized choropleth map

http://www.injusticeeverywhere.com/?p=3333
Unstandardized choropleth maps show numerical data sets. Rather than average the numbers, they all are represented as raw, unadjusted values. Color coding is used to differentiate between sets.
This unstandardized choropleth map shows the 2010 Q3 NPMSRP County-Level Police Misconduct Incidents across the United States.

Nominal area choropleth map

http://my.ilstu.edu/~jrcarter/Geo204/Choro/Tom/
Nominal area choropleth maps are choropleth maps that display nominal data (data that is qualitative, categorical, and classified into groups, with no implicit ordering). Examples of nominal data include hair or eye color, race, ethnicity, religion, etc.
This nominal area choropleth map shows the percent of persons who are Hispanic or Latino (of any race) for Florida, by county. This was taken from the 2000 Census.

Standardized choropleth map

http://www.ij-healthgeographics.com/content/3/1/18/figure/F6
Standardized choropleth maps are those that have been areally averaged (as opposed to unstandardized choropleth maps, which have not been areally averaged). When the numbers have been averaged, the data is then compared (usually by seeing how it is distribution over a specific area). The data is standardized because it is represented as ratios, percentages, rates, decimals, etc.
This is a standardized choropleth map of Bayesian smoothed prevalences in Lower Saxony.

Unclassed choropleth map

http://www.agocg.ac.uk/reports/visual/casestud/dykes/issue3_1.htm
Unclassed choropleth maps are looked at by the majority of cartographers skeptically, because they do not have any data sets to really rely on. Color shadings are used to classify the data, and this is done in proportion to the data values. A color therefore represents a certain data value or range, but there is really no other indicator or clue that helps us in determining what that value actually is. Therefore, unclassed choropleth maps are generally avoided.
This unclassed choropleth map shows the proportion of children ages 0-15. Five unknown classes are used, based on an equal bin interval classification scheme.

Classed choropleth map

http://personal.uncc.edu/lagaro/cwg/color/Choropleth-5Good.gif
A classed choropleth map shows varying statistics that occur within specific boundaries. It follows a pattern of spatial organization of information, without showing trends particular to that information. Rather than use specific, raw data, classed choropleth maps use numerical averages to portray information.
This classed choropleth map shows per pupil expenditure for public education in North Carolina, 1994-1995.

Lorenz Curve, or Accumulative Line Graph

http://ingrimayne.com/econ/AllocatingRationing/MeasuringIncomeDist.html
A Lorenz curve, or Accumulative Line Graph, shows the proportion of the distribution assumed by the bottom "y"% of households. It often compares the % of income (plotted on the y axis) to the % of households (x axis), because it is primarily used in economics. It can also be used to look at assets and general wealth. The Lorenz curve was created in 1905 by Max O. Lorenz, who simply wanted to show the inequalities in the wealth distribution.
This Lorenz curve illustrates the inequalities between percent of income and percent of households.

Stem and leaf plot

http://mainland.cctt.org/mathsummer/JosephBond/StemAndPlots/stem-and-leaf_std.htm
A stem and leaf plot is a way to present numerical data in a graphical format, in order to better visualize distribution. Stem and leaf plots retain the original data to at least two significant digits, and put the data in numerical order. There are two columns (generally) in a stem and leaf plot, that are separated by one vertical line. The stems are on the left, while the leafs are on the right. Stem and leaf plots are useful if plotting relative density and the shape of the data; they are also helpful in finding the mode and any outliers.
This stem and leaf plot shows infant mortality rates in Western Africa.