Standardized choropleth map

http://personal.uncc.edu/lagaro/cwg/color/color_symbol.html
A standardized choropleth map averages the data presented areally to a specific unit. This particular map shows the expenditure per pupil of the public education system of North Carolina, divided by county. An unstandardized map would present a far different picture, being skewed by counties with exceptionally large or small populations. This type of map presents this type of data more accurately than an unstandardized choropleth map would.

Unstandardized choropleth map

http://en.wikipedia.org/wiki/File:Choropleth.gif
An unstandardized choropleth map is one where the data is not areally averaged. This particular map shows the average water use by state of the entire US. This data might be misleading for some viewers who do not understand that the data is not averaged by population, which would create a far different map.

Univariate choropleth map

http://www.agcensus.usda.gov/Publications/2002/Ag_Atlas_Maps/Crops_and_Plants/index.asp
A univariate choropleth map such as this one overlays a single set of data onto the base map. Here we see acres of corn harvested for grain across the US. The use of six groupings for data points makes the map relatively easy to decipher.

Bivariate choropleth

http://www.cartogrammar.com/blog/indiemapper-is-here/
A bivariate choropleth map uses two sets of data, or variables, to color one map based on their correlation. This map, from a site discussing a mapmaking program, shows on the top left a set of data points based on two variables. States are colored based on where the two variables converge in the graph, and thus show the convergence of both variables.

Pie chart

http://vi.sualize.us/view/9edf745d25f9d0b5286f3d980a715686/
This is a pie chart, which, outside of the bar graph, might be the simplest and most recognizable type of visual data representation in existence. Pie charts were part of a movement away from spreadsheet-style data presentation, and the forerunners of the diverse methods of visual representation we have studied in this course. As this specific chart shows, one of the great benefits of a pie chart is in how they simply data into a fairly universally understandable image. Pie charts and their ilk are excellent tools for presenting information to viewers that would be unable to understand facts and figures on paper, and also for making plain data have a stronger impact on its viewer.

Star plot

http://www.itl.nist.gov/div898/handbook/eda/section3/starplot.htm
A star plot allows multiple variables to be compared at once, and then related to the same variables on other star plots. For example, these star plots track data points such as cost, mpg, weight, repair record, and other automobile information. Thinking of the graph as a center point with a line extending in a specific direction for each data point, each specific star plot takes on a shape that can be compared to another within the same criteria. Thus it becomes extremely easy to compare the different automobiles in this image visually.

Correlation matrix

http://www.image.ucar.edu/GSP/Projects/ResearchNuggets.shtml
A correlation matrix shows the correlation of pairs of variables. It is a useful way to compare multiple pairs of variables, and allows a cartographer to visualize several relationships efficiently. These matrices show 20 climate model biases at certain spatial locations. The columns and rows represent the different models, and the diagonal is black because that is where each model intersects with its own data.